Modification and Validation of a Maturity Assessment Tool for Public Health Information System Implementations in Sri Lanka.

INTRODUCTION: Maturity models assess the snapshot view of an organization and simultaneously guides the organization to advance on a road map towards ultimate levels of maturity. The health industry has recently embraced maturity models as a tool to improve the management of health information systems. Most electronic health information systems in Sri Lanka need assessment and monitoring and can benefit vastly by adopting maturity models. This study was conducted to modify and adopt a maturity model for public health institutions in Sri Lanka. METHODS: A review of the literature was done to identify a suitable model to measure the maturity of the public health information system implementations. A Modified Delphi study was then carried out with six experts to adapt the selected maturity tool, Public Health Information Technology (PHIT) maturity index, to the Sri Lankan context. Necessary modifications to the PHIT tool were done according to the comments gathered in the Modified Delphi rounds, and the validity of the tool was established. Finally, Key Informant Interviews were carried out with nine interviewees to qualitatively validate the instrument. RESULTS: The Public Health Information Technology maturity index developed by the University of Maryland, USA, was modified to suit the Sri Lankan context. Comments from the experts were accommodated during the initial rounds of the Modified Delphi study. It further derived the following values, indicating excellent content validity: I-CVI > 0.8 for 57 total items, S-CVI/Avg = 0.988, S-CVI/UA = 0.929 and Free-marginal kappa = 0.95. DISCUSSION AND CONCLUSIONS: Modified and validated PHIT tool can be used to measure the maturity of public health institutions in similar contexts.

Improving the Policy Utility of Cause of Death Statistics in Sri Lanka: An Empirical Investigation of Causes of Out-of-Hospital Deaths Using Automated Verbal Autopsy Methods.

Background: Setting public health policies and effectively monitoring the impact of health interventions requires accurate, timely and complete cause of death (CoD) data for populations. In Sri Lanka, almost half of all deaths occur outside hospitals, with questionable diagnostic accuracy, thus limiting their information content for policy. Objectives: To ascertain whether SmartVA is applicable in improving the specificity of cause of death data for out-of-hospital deaths in Sri Lanka, and hence enhance the value of these routinely collected data for informing public policy debates. Methods: SmartVA was applied to 2610 VAs collected between January 2017 and March 2019 in 22 health-unit-areas clustered in six districts. Around 350 community-health-workers and 50 supervisory-staffs were trained. The resulting distribution of Cause-Specific-Mortality-Fractions (CSMFs) was compared to data from the Registrar-General's-Department (RGD) for out-of-hospital deaths for the same areas, and to the Global-Burden-of-Disease (GBD) estimates for Sri Lanka. Results: Using SmartVA, for only 15% of deaths could a specific-cause not be assigned, compared with around 40% of out-of-hospital deaths currently assigned garbage codes with "very high" or "high" severity. Stroke (M: 31.6%, F: 35.4%), Ischaemic Heart Disease (M: 13.5%, F: 13.0%) and Chronic Respiratory Diseases (M: 15.4%, F: 10.8%) were identified as the three leading causes of home deaths, consistent with the ranking of GBD-Study for Sri Lanka for all deaths, but with a notably higher CSMF for stroke. Conclusions: SmartVA showed greater diagnostic specificity, applicability, acceptability in the Sri Lankan context. Policy formulation in Sri Lanka would benefit substantially with national-wide implementation of VAs.

Strengthening health systems through informatics capacity development among doctors in low-resource contexts: the Sri Lankan experience.

In the process of strengthening health systems, a lack of health-informatics capacity within low- and middle-income country settings is a considerable challenge. Many capacity-development initiatives on health informatics exist, most of which focus on the adoption of eHealth tools by front-line health-care workers. By contrast, there are only a few programmes that focus on empowering medical doctors in low- and middle-income countries to become champions of digital health innovation and adoption. Sri Lanka has a dynamic eHealth ecosystem, resulting largely from the country's community of medical doctors who are also health informaticians. They are the result of a decade-long programme centred on a Master of Science degree course in biomedical informatics, which has trained over 150 medical doctors to date, and has now been extended to a specialist training programme. This paper evaluates this unique capacity-development effort from the perspective of strengthening health systems and how those in other low- and middle-income country contexts may learn from the Sri Lankan experience when implementing capacity-development programmes in health informatics.

'Hybrid Doctors' Can Fast Track the Evolution of a Sustainable e-Health Ecosystem in Low Resource Contexts: The Sri Lankan Experience.

Although e-health is an area recognized as essential in the rapid development of healthcare systems in low resource contexts, many challenges prevent the emergence of an effective e-health ecosystem. Lack in capacity around health informatics is one of the main challenges. Based on a longitudinal case study gathering data pertaining to a master's program in biomedical informatics in Sri Lanka designed for doctors, in this paper we demonstrate that creating 'hybrid doctors' may be the way forward. We illustrate how hybrid doctors conversant in healthcare and information and communication technology (ICT) are able to facilitate the creation of an e-health ecosystem in a way that it would contribute significantly to the ICT driven healthcare reforms. Through this case study we highlight the importance of multidisciplinarity, participatory design, strategic investments, learning that aligns with developmental needs, networking, gaining legitimacy and re-packaging perspectives on 'health informatics capacity development'.

A review of telemedicine interventions in diabetes care.

We reviewed the literature concerning the use of telemedicine interventions in diabetes care. The PubMed database was searched for randomized controlled trials concerning the use of telemedicine for patients with type 1 or type 2 diabetes. A total of 27 articles (studies) met the inclusion criteria. The interventions concerned videoconferencing (n = 8), mobile phones (n = 10) and telephone calls (n = 9). There was metabolic improvement in 23 studies, which was significant in 12 out of 23 (44%). Only two studies (8%) reported a negative clinical outcome. The majority of the studies (n = 19; 70%) employed behavioural therapy as the key intervention. The medium used for interaction in behavioural therapy intervention was videoconferencing (n = 7), mobile phone (n = 4), telephone calls (n = 8), feedback letters (n = 2). Telemedicine appears to be a promising alternative to conventional therapy.

Spatiotemporal antibiotic resistance pattern monitoring using geographical information system based hierarchical cluster analysis.

Bacterial antimicrobial resistance in both the medical and agricultural fields has become a serious problem worldwide. Antibiotic resistant strains of bacteria are an increasing threat to human health, with resistance mechanisms having been described to all known antimicrobials currently available for clinical use. Monitoring the geotemporal variations of antibiotic resistance pattern is crucial factor in planning a successful therapeutic guidelines preventing further emergence of antibiotic resistance. This study is based on the retrospective spatiotemporal analysis of laboratory results of Antibiotic Sensitivity Tests, time stamped with the date and time of the microbiological specimen dispatched to the laboratory. Geographic location of the isolated bacterial colony is specified with the latitude and the longitude of the patient's location. Agglomerative Hierarchical Clustering was performed on antimicrobial resistance findings based on the geographic locations generating series of Heatmaps to visualize the extent of the resistance pattern. Sequential Hierarchical cluster analysis was proven to be effective in visualization of antibiotic resistance using Heatmaps demonstrating the temporal variations of the antibiotic resistance patterns.