Impact of organizational factors on adherence to laboratory testing protocols in adult HIV care in Lusaka, Zambia

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Study Justification:
This study aims to investigate the impact of organizational factors on adherence to laboratory testing protocols in adult HIV care in Lusaka, Zambia. Previous studies have shown the feasibility of large-scale ART programs in resource-limited settings, but the organizational and structural determinants of quality of care have not been thoroughly examined. Understanding these factors is crucial for improving the quality of HIV care and treatment programs.
Highlights:
– CD4 tests were more routinely ordered during initial visits compared to follow-up visits.
– Factors such as physical space, staff turnover, and facility experience with ART were associated with greater adherence to testing protocols.
– Staff experience and burnout had mixed effects on adherence to testing protocols.
– Physical space plays an important role in ensuring high-quality care in resource-limited settings.
– New staff members are more likely to adhere to protocols, highlighting the importance of training and support for healthcare workers.
Recommendations:
– Improve access to physical space and resources in HIV care facilities to support adherence to testing protocols.
– Develop and implement training programs to ensure healthcare workers are knowledgeable and confident in following testing protocols.
– Monitor and address staff turnover and burnout to maintain consistent adherence to testing protocols.
– Conduct further studies using prospective data to confirm the findings and explore additional factors influencing adherence to testing protocols.
Key Role Players:
– Ministry of Health (MOH) in Lusaka Urban District
– Healthcare workers in HIV care and treatment facilities
– Northwestern University
– University of Alabama at Birmingham
– Research Ethics Committee of the University of Zambia
– Clinicians and staff members from various primary health departments (maternal and child health, outpatient, inpatient, labor, HIV care and treatment, tuberculosis)
– CIDRZ (Centre for Infectious Disease Research in Zambia)
Cost Items for Planning Recommendations:
– Resources for improving physical space in HIV care facilities (e.g., renovation, equipment)
– Training programs for healthcare workers
– Monitoring and support systems for addressing staff turnover and burnout
– Data collection and analysis for prospective studies
– Collaboration and coordination between different organizations and departments involved in HIV care and treatment programs

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study uses multivariate regression models and data from 13 urban HIV treatment facilities in Zambia to assess the impact of organizational factors on adherence to laboratory testing protocols. The study provides statistical analysis and presents significant associations between factors such as physical space, staff turnover, staff experience, and adherence to protocols. However, the study is limited to a specific geographic location and time frame, and the data is based on recorded visits and surveys. To improve the strength of the evidence, future studies could include a larger sample size, diverse geographic locations, and prospective data collection to confirm the findings.

Background: Previous operational research studies have demonstrated the feasibility of large-scale public sector ART programs in resource-limited settings. However, organizational and structural determinants of quality of care have not been studied. Methods: We estimate multivariate regression models using data from 13 urban HIV treatment facilities in Zambia to assess the impact of structural determinants on health workers’ adherence to national guidelines for conducting laboratory tests such as CD4, hemoglobin and liver function and WHO staging during initial and follow-up visits as part of Zambian HIV care and treatment program. Results: CD4 tests were more routinely ordered during initial history and physical (IHP) than follow-up (FUP) visits (93.0 % vs. 85.5 %; p<0.01). More physical space, higher staff turnover and greater facility experience with ART was associated with greater odds of conducting tests. Higher staff experience decreased the odds of conducting CD4 tests in FUP (OR 0.93; p<0.05) and WHO staging in IHP visit (OR 0.90; p<0.05) but increased the odds of conducting hemoglobin test in IHP visit (OR 1.05; p<0.05). Higher staff burnout increased the odds of conducting CD4 test during FUP (OR 1.14; p<0.05) but decreased the odds of conducting hemoglobin test in IHP visit (0.77; p<0.05) and CD4 test in IHP visit (OR 0.78; p<0.05). Conclusion: Physical space plays an important role in ensuring high quality care in resource-limited setting. In the context of protocolized care, new staff members are likely to be more diligent in following the protocol verbatim rather than relying on memory and experience thereby improving adherence. Future studies should use prospective data to confirm the findings reported here. © 2012 Deo et al.; licensee BioMed Central Ltd.

Of the more than 150 HIV care and treatment facilities run by MOH in Lusaka Urban District, we focused on 13 because of the similarity in geographic location, conditions of service-delivery for these clinics and, availability of data on staff burnout in these facilities from a healthcare worker survey [9] conducted between March and June 2007. As most of these clinics had been providing HIV care for over 6 months (one clinic only 5 months), the effects of initial scale-up were minimized. Our study was approved by the institutional review boards at Northwestern University, University of Alabama at Birmingham, and the Research Ethics Committee of the University of Zambia. We included all recorded visits of adult patients (aged 16 years or more) diagnosed with HIV and enrolled in care during the calendar year 2007. This coincides with the time frame of the healthcare worker survey [9]. Data on predictors related to staff motivation (burnout, experience, absenteeism and turnover), were obtained from the healthcare worker survey [9] in various primary health departments (maternal and child health, outpatient, inpatient, labor, HIV care and treatment, tuberculosis) in Lusaka Urban District in 2007. Approximately 500, anonymous responses from 13 facilities were received and analyzed. Some of the relevant questions are reproduced in Table ​Table11. Description of predictor variables and their data sources In addition to obtaining data on the outcomes of the study, electronic medical records (SmartCare database) were used to obtain data on the number of daily visits to facilities. The study did not require identification of patients; rather the primary record marker was the type of visit – ART initiation, ART follow up etc. Visit information was extracted based on inclusion / exclusion criteria mentioned above and all patient identifiers were removed. Records of overtime payments were used to calculate the number of shifts worked by nurses and clinical officers in ART clinics. In 2007, all staff members working in the ART clinics were deputed from other departments and worked overtime in the ART clinics. Administrative databases within CIDRZ and MOH were used to calculate the length of time since initiation of ART program services at each facility. Architectural plans of each facility were used to calculate the total floor area of each clinic, to determine calculation of physical space. Owing to shortages of physicians, clinical officers (analogous to physician’s assistants in the U.S.) and nurses delivered majority of healthcare services in our setting. To ensure a minimum standard of care, clinicians followed visit-specific protocols (initial visit form, routine follow-up form etc.) that reflected national treatment guidelines. These forms were designed to guide clinicians through initial evaluation of newly enrolling patients and all subsequent follow-up visits. In this study, we constructed dichotomous variables to indicate whether appropriate laboratory / clinical tests were conducted at each of these visits. Initial History and Physical (IHP) visit: At the initial visit, we examined whether patients were correctly assessed according to WHO and national guidelines. In addition we examined whether baseline laboratory investigations, such as CD4, hemoglobin, liver function tests were properly carried out in accordance with WHO staging and national guidelines. We gave a positive credit to the facility if results were recorded in the patient’s chart within 4 weeks before and after the patient’s visit. Follow-up (FUP) visits: We chose CD4 test as a measure of adherence to follow-up visit protocol because CD4 count is a key clinical indicator of treatment response (for those on treatment) and disease progression (for those not on treatment). Thus, it provides a better measure of adherence to protocol across all patients compared to other non-compulsory tests such as hemoglobin and liver function [22]. We measured whether repeat CD4 testing was ordered within 6 months of the previous test. To account for variability in patient attendance to scheduled visits, we developed the following rule. For each follow-up visit, we expected a CD4 count test to be done if there was no CD4 result entered in the database in the preceding 160 days. For each visit where CD4 was expected, we considered the CD4 test done if the result was recorded in the patient’s chart within four weeks after the visit. Our quality measure was calculated as the total CD4 tests done in each month, divided by the sum of visits where a CD4 was expected and not expected but done in each month for each facility. For sensitivity analysis, we repeated the analysis with 180 days time window. We also repeated the analysis with a different definition of done as either a tick mark on the patient’s chart or a result within 4 weeks. In addition, we also counted the CD4 test as done in follow-up visits where it was not expected according to our definition above. We did not have access to the identity of health care workers involved in provision of care to individual patients. Thus, we could not analyze the difference in adherence to protocols at the worker level but could only infer these differences at the facility level. Facility level measures for staff burnout, staff experience, staff absenteeism and staff turnover were calculated by taking the median of individual responses to the staff motivation survey from that facility. Monthly staffing ratio was calculated by dividing the patient visits to the ART department by full time equivalent (FTE) staff shifts. This included nurses, physicians, clinical officers, technicians and pharmacists. A measure of physical space was calculated by dividing the floor area of ART department by the total patient visits during 2007. An alternative measure using average patient visits per day for each month did not alter the results substantially. In our setting, more than 90 % of the space was used for delivery of care and the rest for administrative tasks. Clinic age was calculated as the time since the initiation of ART program services as of January 2007 (Table ​(Table2).2). All predictors, except those constructed from health worker survey, pertained to ART services. The predictors derived from the survey included staff members belonging to other departments as well. Summary statistics of predictor variables Each column shows the median value for each variable by site. Measures of these predictor variables were held constant for each site during the study period. We ran multi-level logistic regression models using SAS GLIMMIX procedure for visit level outcome variables. We used facility-month combinations to define the hierarchical structure, intercept as a random effect, and other predictors as fixed effects. We developed and analyzed two model variants (nested within each other) to assess the incremental impact of different predictor variables: (i) Model 1 included Staff Experience, Staff Turnover, Space per visit, Clinic Age, Visits per shift, (ii) Model 2 included all the above predictors and Staff Absenteeism and Staff Burnout. We did not include burnout in the first model since it was assessed using a single item from the healthcare worker survey, whose validation with a more accepted Maslach Burnout Inventory has been conducted outside of resource-limited setting [23]. Similarly, we did not include absenteeism in the first model since it itself can be considered as an outcome of other staff related variables and its direct impact on health outcomes was, a priori, not clear. Since the results were not very different for the two model variants and because the coefficients of absenteeism and burnout were significant, we present the results of Model 2. All analyses performed using SAS/STAT software, Version 9.1 (Cary, NC, USA).

Based on the provided information, it seems that the focus of the study is on organizational factors that impact adherence to laboratory testing protocols in adult HIV care. While the study does not directly address maternal health, there are potential innovations that can be derived from the findings to improve access to maternal health. Here are some recommendations:

1. Improve physical space: The study found that greater physical space was associated with greater odds of conducting laboratory tests. This suggests that ensuring adequate physical space in maternal health facilities can improve access to necessary tests and screenings for pregnant women.

2. Minimize staff turnover: The study found that higher staff turnover was associated with lower adherence to laboratory testing protocols. To improve access to maternal health, efforts should be made to minimize staff turnover in maternal health facilities. This can be achieved through strategies such as providing competitive salaries, offering professional development opportunities, and creating a supportive work environment.

3. Enhance staff experience: The study found that higher staff experience was associated with both positive and negative impacts on adherence to laboratory testing protocols. To improve access to maternal health, it is important to provide ongoing training and support for staff to ensure they have the necessary skills and knowledge to effectively conduct tests and screenings.

4. Address staff burnout: The study found that higher staff burnout was associated with lower adherence to laboratory testing protocols. To improve access to maternal health, it is crucial to address staff burnout and promote staff well-being. This can be done through measures such as implementing work-life balance initiatives, providing mental health support, and fostering a positive work environment.

5. Utilize electronic medical records: The study mentioned the use of electronic medical records to obtain data on patient visits and test results. Implementing electronic medical records in maternal health facilities can improve access to maternal health by facilitating efficient data management, reducing paperwork, and enabling better coordination of care.

It is important to note that these recommendations are derived from the study’s findings on organizational factors in HIV care. Further research and adaptation may be needed to specifically address access to maternal health.
AI Innovations Description
The recommendation that can be developed into an innovation to improve access to maternal health based on the provided description is to implement a protocolized care system for maternal health services. This protocolized care system should include visit-specific protocols that guide healthcare providers in conducting necessary laboratory and clinical tests during initial and follow-up visits for pregnant women.

By implementing this protocolized care system, healthcare providers will be more likely to adhere to national guidelines for conducting laboratory tests, such as CD4, hemoglobin, and liver function tests, during maternal health visits. This will ensure that pregnant women receive the necessary tests and evaluations according to WHO and national guidelines.

Additionally, the protocolized care system should also consider organizational factors that impact adherence to protocols, such as physical space, staff turnover, staff experience, and staff burnout. Providing adequate physical space for maternal health services can contribute to high-quality care in resource-limited settings. New staff members are likely to be more diligent in following protocols, which can improve adherence to guidelines. However, staff burnout should be addressed as it can negatively impact adherence to protocols.

Implementing this protocolized care system for maternal health services can help improve access to quality care for pregnant women, ensuring that they receive the necessary tests and evaluations according to guidelines. It is important to conduct further studies using prospective data to confirm the findings and assess the effectiveness of this innovation.
AI Innovations Methodology
The study mentioned in the description focuses on the impact of organizational factors on adherence to laboratory testing protocols in adult HIV care in Lusaka, Zambia. The goal is to understand how structural determinants, such as physical space, staff turnover, and staff experience, affect health workers’ adherence to national guidelines for conducting laboratory tests.

To simulate the impact of recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Identify the key recommendations: Based on the findings of the study, identify the key recommendations that could improve access to maternal health. For example, if physical space was found to play an important role in ensuring high-quality care, a recommendation could be to allocate more physical space to maternal health facilities.

2. Define the indicators: Determine the indicators that will be used to measure the impact of the recommendations on improving access to maternal health. These indicators could include the number of maternal health visits, the availability of essential maternal health services, and the satisfaction of patients with the quality of care.

3. Collect baseline data: Collect baseline data on the selected indicators before implementing the recommendations. This will provide a benchmark against which the impact of the recommendations can be measured.

4. Implement the recommendations: Implement the identified recommendations in selected maternal health facilities. This could involve allocating more physical space, improving staff experience through training programs, or addressing staff burnout through support systems.

5. Monitor and evaluate: Continuously monitor and evaluate the impact of the implemented recommendations on the selected indicators. This could involve collecting data on the indicators at regular intervals after the implementation of the recommendations.

6. Analyze the data: Analyze the collected data to assess the impact of the recommendations on improving access to maternal health. This could involve comparing the data collected after the implementation of the recommendations with the baseline data.

7. Draw conclusions and make recommendations: Based on the analysis of the data, draw conclusions about the effectiveness of the recommendations in improving access to maternal health. Make recommendations for further improvements or adjustments to the recommendations based on the findings.

8. Disseminate the findings: Share the findings of the simulation study with relevant stakeholders, such as policymakers, healthcare providers, and researchers. This will contribute to the knowledge base on improving access to maternal health and inform future interventions.

By following this methodology, it will be possible to simulate the impact of recommendations on improving access to maternal health based on the findings of the study on organizational factors in HIV care in Lusaka, Zambia.

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