Factors Associated with HIV Infection in Married or Cohabitating Couples in Kenya: Results from a Nationally Representative Study

BACKGROUND: In order to inform prevention programming, we analyzed HIV discordance and concordance within couples in the Kenya AIDS Indicator Survey (KAIS) 2007. METHODS: KAIS was a nationally representative population-based sero-survey that examined demographic and behavioral indicators and serologic testing for HIV, HSV-2, syphilis, and CD4 cell counts in 15,853 consenting adults aged 15-64 years. We analyzed interview and blood testing data at the sexual partnership level from married or cohabitating couples. Multivariable regression models were used to identify factors independently associated with HIV discordant and concordant status. RESULTS: Of 3256 couples identified in the survey, 2748 (84.4%) had interview and blood testing data. Overall, 3.8% of couples were concordantly infected with HIV, and in 5.8% one partner was infected, translating to 338,000 discordant couples in Kenya. In 83.6% of HIV-infected Kenyans living in married or cohabitating couples neither partner knew their HIV status. Factors independently associated with HIV-discordance included young age in women (AOR 1.5, 95% CI: 1.2-1.8; p<0.0001), increasing number of lifetime sexual partners in women (AOR 1.5, 95% CI: 1.3-1.8; p<0.0001), HSV-2 infection in either or both partners (AOR 4.1, 95% CI: 2.3-7.2; p<0.0001), and lack of male circumcision (AOR 1.6, 95% CI: 1.0-2.5; p = 0.032). Independent factors for HIV-concordance included HSV-2 infection in both partners (AOR 6.5, 95% CI: 2.3-18.7; p = 0.001) and lack of male circumcision (AOR 1.8, 95% CI: 1.0-3.3; p = 0.043). CONCLUSIONS: Couple prevention interventions should begin early in relationships and include mutual knowledge of HIV status, reduction of outside sexual partners, and promotion of male circumcision among HIV-uninfected men. Mechanisms for effective prevention or suppression of HSV-2 infection are also needed

Evaluation of Health IT in Low-Income Countries

Low and middle income countries (LMICs) bear a disproportionate burden of major global health challenges. Health IT could be a promising solution in these settings but LMICs have the weakest evidence of application of health IT to enhance quality of care. Various systematic reviews show significant challenges in the implementation and evaluation of health IT. Key barriers to implementation include lack of adequate infrastructure, inadequate and poorly trained health workers, lack of appropriate legislation and policies and inadequate financial 333indicating the early state of generation of evidence to demonstrate the effectiveness of health IT in improving health outcomes and processes. The implementation challenges need to be addressed. The introduction of new guidelines such as GEP-HI and STARE-HI, as well as models for evaluation such as SEIPS, and the prioritization of evaluations in eHealth strategies of LMICs provide an opportunity to focus on strategic concepts that transform the demands of a modern integrated health care system into solutions that are secure, efficient and sustainabl

Inconsistencies between recorded opportunistic infections and WHO HIV staging in western Kenya

Opportunistic infections (OIs) are the main cause of morbidity and mortality among patients with HIV in developing countries. It is therefore critical that accurate diagnoses are made and that they are correctly recorded and managed. We reviewed 200 randomly selected records of clinical encounters with HIV infected pregnant women attending the ante-natal care (ANC) clinic in July 2012 at the Jaramogi Oginga Odinga Teaching and Referral Hospital in Kenya. None of the clients in WHO stage 4 and 2.8% of those in WHO stage 3 had a new OI diagnosis recorded during the clinical encounter. This data suggests current under-recording of OIs and the inconsistency between WHO staging and OI diagnosis. Structured methods such as SNOMED CT have the potential to improve complete and accurate recording of OIs which, in turn, enable automatedand accurate WHO staging

A structured approach to recording AIDS-defining illnesses in Kenya: A SNOMED CT based solution

Several studies conducted in sub-Saharan Africa (SSA) have shown that routine clinical data in HIV clinics often have errors. Lack of structured and coded documentation of diagnosis of AIDS defining illnesses (ADIs) can compromise data quality and decisions made on clinical care. We used a structured framework to derive a reference set of concepts and terms used to describe ADIs. The four sources used were: (i) CDC/Accenture list of opportunistic infections, (ii) SNOMED Clinical Terms (SNOMED CT), (iii) Focus Group Discussion (FGD) among clinicians and nurses attending to patients at a referral provincial hospital in western Kenya, and (iv) chart abstraction from the Maternal Child Health (MCH) and HIV clinics at the same hospital. Using the January 2014 release of SNOMED CT, concepts were retrieved that matched terms abstracted from approach iii & iv, and the content coverage assessed. Post-coordination matching was applied when needed. The final reference set had 1054 unique ADI concepts which were described by 1860 unique terms. Content coverage of SNOMED CT was high (99.9% with pre-coordinated concepts; 100% with post-coordination). The resulting reference set for ADIs was implemented as the interface terminology on OpenMRS data entry forms. Different sources demonstrate complementarity in the collection of concepts and terms for an interface terminology. SNOMED CT provides a high coverage in the domain of ADIs. Further work is needed to evaluate the effect of the interface terminology on data quality and quality of car

The effect of electronic medical record-based clinical decision support on HIV care in resource-constrained settings: A systematic review

Background: It is estimated that one million people infected with HIV initiate anti-retroviral therapy (ART) in resource-constrained countries annually. This occurs against a background of overburdened health workers with limited skills to handle rapidly changing treatment standards and guidelines hence compromising quality of care. Electronic medical record (EMR)-based clinical decision support systems (CDSS) are considered a solution to improve quality of care. Little evidence, however, exists on the effectiveness of EMR-based CDSS on quality of HIV care and treatment in resource-constrained settings. Objective: The aim of this systematic review was to identify original studies on EMR-based CDSS describing process and outcome measures as well as reported barriers to their implementation in resource-constrained settings. We characterized the studies by guideline adherence, data and process, and barriers to CDSS implementation. Methods: Two reviewers independently assessed original articles from a search of the MEDLINE, EMBASE, CINAHL and Global Health Library databases until January 2012. The included articles were those that evaluated or described the implementation of EMR-based CDSS that were used in HIV care in low-income countries. Results: A total of 12 studies met the inclusion criteria, 10 of which were conducted in sub-Saharan Africa and 2 in the Caribbean. None of the papers described a strong (randomized controlled) evaluation design. Guideline adherence: One study showed that ordering rates for CD4 tests were significantly higher when reminders were used. Data and process: Studies reported reduction in data errors, reduction in missed appointments, reduction in missed CD4 results and reduction in patient waiting time. Two studies showed a significant increase in time spent by clinicians on direct patient care. Barriers to CDSS implementation: Technical infrastructure problems such as unreliable electric power and erratic Internet connectivity, clinicians' limited computer skills and failure by providers to comply with the reminders are key impediments to the implementation and effective use of CDSS. The limited number of evaluation studies, the basic and heterogeneous study designs, and varied outcome measures make it difficult to meaningfully conclude on the effectiveness of CDSS on quality of HIV care and treatment in resource-limited settings. High quality evaluation studies are needed. Factors specific to implementation of EMR-based CDSS in resource-limited setting should be addressed before such countries can demonstrate its full benefits. More work needs to be done to overcome the barriers to EMR and CDSS implementation in developing countries such as technical infrastructure and care providers' computer illiteracy. However, simultaneously evaluating and describing CDSS implementation strategies that work can further guide wise investments in their wider rollout. Published by Elsevier Ireland Lt

Better adherence to pre-antiretroviral therapy guidelines after implementing an electronic medical record system in rural Kenyan HIV clinics: a multicenter pre–post study

Introduction: The monitoring of pre-antiretroviral therapy (pre-ART) is a key indicator of HIV quality of care. This study investigated the association of an electronic medical record system (EMR) with adherence to pre-ART guidelines in rural HIV clinics in Kenya. Methods: A retrospective study was carried out to assess the quality of pre-ART care using three indicators: (1) the performance of a baseline CD4 test, (2) time from enrollment in care to first CD4 test, and (3) time from baseline CD4 to second CD4 test. A comparison of these indicators was made pre and post the introduction of an EMR system in 17 rural HIV clinics. Results: A total of 18 523 patients were receiving pre-ART care, of whom 38.8% in the paper group had had at least one CD4 test compared to 53.4% in the EMR group (p < 0.001). The adjusted odds of performing a CD4 test in clinics using an EMR was 1.59 (95% confidence interval 1.49–1.69). The median time from enrolment into HIV care to first CD4 test was 1.40 months (interquartile range (IQR) 0.47–4.87) for paper vs. 0.93 months (IQR 0.43–3.37) for EMR. The median time from baseline to first CD4 follow-up was 7.5 months (IQR 5.97–10.73) for paper and 6.53 months (IQR 5.57–7.87) for EMR. Conclusion: The use of the EMR system was associated with better compliance to HIV guidelines for pre-ART care. EMRs have a potential positive impact on quality of care for HIV patients in resource-constrained settings

Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2

Introduction:Developing countries are increasingly strengthening national health information systems (HIS) for evidence-based decision-making. However, the inability to report indicator data automatically from electronic medical record systems (EMR) hinders this process. Data are often printed and manually re-entered into aggregate reporting systems. This affects data completeness, accuracy, reporting timeliness, and burdens staff who support routine indicator reporting from patient-level data. Method: After conducting a feasibility test to exchange indicator data from Open Medical Records System (OpenMRS) to District Health Information System version 2 (DHIS2), we conducted a field test at a health facility in Kenya. We configured a field-test DHIS2 instance, similar to the Kenya Ministry of Health (MOH) DHIS2, to receive HIV care and treatment indicator data and the KenyaEMR, a customized version of OpenMRS, to generate and transmit the data from a health facility. After training facility staff how to send data using DHIS2 reporting module, we compared completeness, accuracy and timeliness of automated indicator reporting with facility monthly reports manually entered into MOH DHIS2. Results: All 45 data values in the automated reporting process were 100% complete and accurate while in manual entry process, data completeness ranged from 66.7% to 100% and accuracy ranged from 33.3% to 95.6% for seven months (July 2013-January 2014). Manual tally and entry process required at least one person to perform each of the five reporting activities, generating data from EMR and manual entry required at least one person to perform each of the three reporting activities, while automated reporting process had one activity performed by one person. Manual tally and entry observed in October 2013 took 375 minutes. Average time to generate data and manually enter into DHIS2 was over half an hour (M=32.35 mins, SD=0.29) compared to less than a minute for automated submission (M=0.19 mins, SD=0.15). Discussion and Conclusion: The results indicate that indicator data sent electronically from OpenMRS-based EMR at a health facility to DHIS2 improves data completeness, eliminates transcription errors and delays in reporting, and reduces the reporting burden on human resources. This increases availability of quality indicator data using available resources to facilitate monitoring service delivery and measuring progress towards set goals

Automating indicator data reporting from health facility EMR to a national aggregate data system in Kenya: An Interoperability field-test using OpenMRS and DHIS2

Introduction: Developing countries are increasingly strengthening national health information systems (HIS) for evidence-based decision-making. However, the inability to report indicator data automatically from electronic medical record systems (EMR) hinders this process. Data are often printed and manually re-entered into aggregate reporting systems. This affects data completeness, accuracy, reporting timeliness, and burdens staff who support routine indicator reporting from patient-level data.  Method: After conducting a feasibility test to exchange indicator data from Open Medical Records System (OpenMRS) to District Health Information System version 2 (DHIS2), we conducted a field test at a health facility in Kenya. We configured a field-test DHIS2 instance, similar to the Kenya Ministry of Health (MOH) DHIS2, to receive HIV care and treatment indicator data and the KenyaEMR, a customized version of OpenMRS, to generate and transmit the data from a health facility. After training facility staff how to send data using the module, we compared completeness, accuracy and timeliness of automated indicator reporting with facility monthly reports manually entered into MOH DHIS2.Results: All 45 data values in the automated reporting process were 100% complete and accurate while in manual entry process, data completeness ranged from 66.7% to 100% and accuracy ranged from 33.3% to 95.5% for seven months (July 2013-January 2014). Manual tally and entry process required at least one person to perform each of the five reporting activities, generating data from EMR and manual entry required at least one person to perform each of the three reporting activities, while automated reporting process had one activity performed by one person. Manual tally and entry observed in October 2013 took 375 minutes. Average time to generate data and manually enter into DHIS2 was over half an hour (M=32.35 mins, SD=0.29) compared to less than a minute for automated submission (M=0.19 mins, SD=0.15).Discussion and Conclusion: The results indicate that indicator data sent electronically from OpenMRS-based EMR at a health facility to DHIS2 improves data completeness, eliminates transcription errors and delays in reporting, and reduces the reporting burden on human resources. This increases availability of quality indicator data using available resources to facilitate monitoring service delivery and measuring progress towards set goals