The influence of family physicians within the South African district health system: A cross-sectional study

Annals of Family Medicine, Volume 16, No. 1, Year 2018

Ukuhunyushwa

PURPOSE Evidence of the influence of family physicians on health care is required to assist managers and policy makers with human resource planning in Africa. The international argument for family physicians derives mainly from research in high-income countries, so this study aimed to evaluate the influence of family physicians on the South African district health system. METHODS We conducted a cross-sectional observational study in 7 South African provinces, comparing 15 district hospitals and 15 community health centers (primary care facilities) with family physicians and the same numbers without family physicians. Facilities with and without family physicians were matched on factors such as province, setting, and size. RESULTS Among district hospitals, those with family physicians generally scored better on indicators of health system performance and clinical processes, and they had significantly fewer modifiable factors associated with pediatric mortality (mean, 2.2 vs 4.7, P =.049). In contrast, among community health centers, those with family physicians generally scored more poorly on indicators of health system performance and clinical processes, with significantly poorer mean scores for continuity of care (2.79 vs 3.03; P =.03) and coordination of care (3.05 vs 3.51; P =.02). CONCLUSIONS In this study, having family physicians on staff was associated with better indicators of performance and processes in district hospitals but not in community health centers. The latter was surprising and is inconsistent with the global literature, suggesting that further research is needed on the influence of family physicians at the primary care level. We conducted a cross-sectional, observational study to compare community health centers (primary care facilities) and district hospitals with vs without family physicians. Use of family physicians was not randomized as the creation and filling of family physician posts were predetermined by local policy and service requirements. The group of facilities with family physicians had had a family physician in a designated post for a minimum of 2 years. The comparison group consisted of facilities that did not have a family physician post on staff or any other exposure to a family physician. We used the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement’s checklist23 to guide this research. We created a conceptual framework (Figure 1) to inform our approach to designing the study and determining the data collection instruments. In this framework, structure refers to issues of governance and economics that are largely affected by changes in policy. Health service processes are subdivided into generic (cross-cutting organizational processes), targeted (aimed at a specific program or condition), or clinical (services at the level of the patient). Generic and targeted processes can affect health system performance, which also influences the quality of clinical processes that in turn affect clinical outcomes. Family physicians were seen as a generic intervention as they were not limited to a specific program or condition and could have impact broadly on health system performance and clinical processes. We assessed 4 key aspects of primary health system performance: accessibility, coordination, comprehensiveness, and continuity.26 The key clinical processes were drawn from South Africa’s quadruple burden of disease and public health issues: HIV/AIDS and tuberculosis; violence and injury; maternal and child health; and noncommunicable diseases.17 Conceptual framework of the study (a modified Donabedian causal chain).24,25 This study was conducted in the district health system of the South African public sector in 7 of the country’s 9 provinces. (See Supplemental Appendix 2 at http://www.AnnFamMed.org/content/16/1/28/suppl/DC1 for a brief description of the South African district health system.) We used a clinical process indicator (the diabetes management score) and a health outcome indicator (the facility-based perinatal mortality rate) for calculation of study sample size, given that family physicians are reported to have a positive impact on these indicators, with an earlier study providing standard deviations and estimates of likely effect size.27 A sample size of 14 community health centers in each group gave 80% power to detect an effect size of 10% in the diabetes management score (SD, 13%) with a possible 5% type 1 error.27 A sample size of 14 district hospitals in each arm gave 80% power to detect an effect size of 8.4 perinatal deaths per 1,000 births in perinatal mortality rate (SD, 7.91) with a 5% type 1 error.27 We therefore chose a final sample size of 15 district hospitals and 15 community health centers in each group (with and without family physicians, for 60 facilities in total) to have sufficient power and to allow for some loss of facilities or incomplete data collection. Seven out of the 9 provinces were included in the study as determined by the educational footprint of the 6 participating universities that train family physicians in South Africa. We obtained a complete list of district hospitals and community health centers from the National Department of Health. With the assistance of the participating universities, this list was split into lists of facilities with and facilities without family physicians, which were then randomly reordered. Starting at the top of the randomly ordered lists, we selected 2 district hospitals and 2 community health centers with family physicians from each province to give 14 district hospitals and 14 community health centers. Each was then matched with a facility without family physicians from the other list using criteria shown in Table 1. One additional facility for each group was selected from the Western Cape Province, where the study was based, to arrive at the intended number of 15 facilities per group. (Supplemental Appendix 3, at http://www.AnnFamMed.org/content/16/1/28/suppl/DC1, shows the facility sampling selection process.) Matching Criteria by Facility Type For study outcomes, we selected a set of indicators that we expected would reflect the influence of the family physician on clinical processes, health system performance, and clinical outcomes (Figure 1). The selection of corresponding data collection instruments/ tools (Table 2)28–35 was dependent on the availability of reliable and valid routinely collected data or existing tools, the feasibility of collecting data, the different scope of practice in district hospitals and community health centers, and an a priori consensus between the researchers in the participating academic departments. Instruments/Tools Used for Data Collection CDM = chronic disease management; COPD = chronic obstructive pulmonary disease; MRC = Medical Research Council of South Africa; PCAT = Primary Care Assessment Tool; PIP = Problem Identification Program; WHO = World Health Organization. We trained 4 teams with a total of 16 fieldworkers (11 health professionals and 5 assistants with previous experience in research data collection) to collect data in the 7 provinces according to a detailed fieldwork protocol (Supplemental Appendix 4 at http://www.AnnFamMed.org/content/16/1/28/suppl/DC1). Fieldworkers were interviewed before appointment. Training was facilitated by the lead investigator (K.B.vP.) over 2 to 3 days, and consisted of face-to-face training, role playing, and practical evaluation in the field. Each team was led by a health professional and supervised by an academic family physician attached to a participating university. The teams also interacted remotely with the lead investigator (K.B.vP.) via telephone, e-mail, and a communication application (WhatsApp). Facility-level data were collected between June 2015 and March 2016, and then captured with EpiData version 3.1 (EpiData Software) via a double-entry method and using checks to minimize data entry errors.36 We then imported the data from EpiData into Microsoft Excel (Microsoft Inc) and used SPSS version 23 (IBM Corp)37 to conduct the analysis in consultation with a biostatistician. Data analysis commenced with descriptive statistics for the facilities. Subsequently, the independent samples t test for equality of means was used to compare means between the groups with and without family physicians (continuous dependent variables, see Table 2 for detail on the data collected). For those means found to be significantly different, we performed regression analysis using a generalized linear model to control for the effect of confounders. Confounding variables for health system performance were levels of staff (professional nurses, junior and senior physicians) and distance from a referral hospital. Confounding variables for clinical processes were the presence of outreach to the district health system facility (from the general specialties at the referral hospitals) and bed utilization rate (as proxy of district hospital inpatient workload). This study was approved by the Health Research Ethics Committee (Medical), Stellenbosch University (reference S15/01/003) and by each partner institution. The 7 provincial health authorities and research committees also gave permission to access facilities across the study setting (Supplemental Appendix 5 at http://www.AnnFamMed.org/content/16/1/28/suppl/DC1).

I-AI Digest

Study Justification:

– The purpose of this study was to provide evidence of the influence of family physicians on the South African district health system.
– The study aimed to assist managers and policy makers with human resource planning in Africa by evaluating the impact of family physicians on health care.

Study Highlights:

– The study conducted a cross-sectional observational study in 7 South African provinces, comparing district hospitals and community health centers with and without family physicians.
– Among district hospitals, those with family physicians generally scored better on indicators of health system performance and clinical processes, and had fewer modifiable factors associated with pediatric mortality.
– However, among community health centers, those with family physicians generally scored more poorly on indicators of health system performance and clinical processes, with significantly poorer scores for continuity of care and coordination of care.
– The findings were surprising and inconsistent with the global literature, suggesting a need for further research on the influence of family physicians at the primary care level.

Recommendations:

– Further research is needed to understand the influence of family physicians at the primary care level.
– Policy makers should consider the potential impact of family physicians on health system performance and clinical processes when planning human resource allocation in the district health system.

Key Role Players:

– Managers and policy makers in the South African district health system.
– Health professionals, including family physicians, working in district hospitals and community health centers.
– Researchers and academics involved in conducting further research on the influence of family physicians.

Cost Items for Planning Recommendations:

– Funding for additional research on the influence of family physicians at the primary care level.
– Budget allocation for the recruitment and training of family physicians in district hospitals and community health centers.
– Resources for improving health system performance and clinical processes in facilities with family physicians, based on the study findings.

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a cross-sectional observational study conducted in 7 South African provinces. The study compared district hospitals and community health centers with and without family physicians. The facilities were matched on factors such as province, setting, and size. The study found that district hospitals with family physicians generally scored better on indicators of health system performance and clinical processes, while community health centers with family physicians generally scored more poorly on these indicators. However, the study acknowledges that the findings for community health centers are surprising and inconsistent with the global literature. The study suggests that further research is needed on the influence of family physicians at the primary care level. To improve the strength of the evidence, future studies could consider using a randomized controlled trial design to minimize bias and establish causality. Additionally, increasing the sample size and including a more diverse range of facilities could enhance the generalizability of the findings.

Abstract

We conducted a cross-sectional, observational study to compare community health centers (primary care facilities) and district hospitals with vs without family physicians. Use of family physicians was not randomized as the creation and filling of family physician posts were predetermined by local policy and service requirements. The group of facilities with family physicians had had a family physician in a designated post for a minimum of 2 years. The comparison group consisted of facilities that did not have a family physician post on staff or any other exposure to a family physician. We used the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement’s checklist23 to guide this research. We created a conceptual framework (Figure 1) to inform our approach to designing the study and determining the data collection instruments. In this framework, structure refers to issues of governance and economics that are largely affected by changes in policy. Health service processes are subdivided into generic (cross-cutting organizational processes), targeted (aimed at a specific program or condition), or clinical (services at the level of the patient). Generic and targeted processes can affect health system performance, which also influences the quality of clinical processes that in turn affect clinical outcomes. Family physicians were seen as a generic intervention as they were not limited to a specific program or condition and could have impact broadly on health system performance and clinical processes. We assessed 4 key aspects of primary health system performance: accessibility, coordination, comprehensiveness, and continuity.26 The key clinical processes were drawn from South Africa’s quadruple burden of disease and public health issues: HIV/AIDS and tuberculosis; violence and injury; maternal and child health; and noncommunicable diseases.17 Conceptual framework of the study (a modified Donabedian causal chain).24,25 This study was conducted in the district health system of the South African public sector in 7 of the country’s 9 provinces. (See Supplemental Appendix 2 at http://www.AnnFamMed.org/content/16/1/28/suppl/DC1 for a brief description of the South African district health system.) We used a clinical process indicator (the diabetes management score) and a health outcome indicator (the facility-based perinatal mortality rate) for calculation of study sample size, given that family physicians are reported to have a positive impact on these indicators, with an earlier study providing standard deviations and estimates of likely effect size.27 A sample size of 14 community health centers in each group gave 80% power to detect an effect size of 10% in the diabetes management score (SD, 13%) with a possible 5% type 1 error.27 A sample size of 14 district hospitals in each arm gave 80% power to detect an effect size of 8.4 perinatal deaths per 1,000 births in perinatal mortality rate (SD, 7.91) with a 5% type 1 error.27 We therefore chose a final sample size of 15 district hospitals and 15 community health centers in each group (with and without family physicians, for 60 facilities in total) to have sufficient power and to allow for some loss of facilities or incomplete data collection. Seven out of the 9 provinces were included in the study as determined by the educational footprint of the 6 participating universities that train family physicians in South Africa. We obtained a complete list of district hospitals and community health centers from the National Department of Health. With the assistance of the participating universities, this list was split into lists of facilities with and facilities without family physicians, which were then randomly reordered. Starting at the top of the randomly ordered lists, we selected 2 district hospitals and 2 community health centers with family physicians from each province to give 14 district hospitals and 14 community health centers. Each was then matched with a facility without family physicians from the other list using criteria shown in Table 1. One additional facility for each group was selected from the Western Cape Province, where the study was based, to arrive at the intended number of 15 facilities per group. (Supplemental Appendix 3, at http://www.AnnFamMed.org/content/16/1/28/suppl/DC1, shows the facility sampling selection process.) Matching Criteria by Facility Type For study outcomes, we selected a set of indicators that we expected would reflect the influence of the family physician on clinical processes, health system performance, and clinical outcomes (Figure 1). The selection of corresponding data collection instruments/ tools (Table 2)28–35 was dependent on the availability of reliable and valid routinely collected data or existing tools, the feasibility of collecting data, the different scope of practice in district hospitals and community health centers, and an a priori consensus between the researchers in the participating academic departments. Instruments/Tools Used for Data Collection CDM = chronic disease management; COPD = chronic obstructive pulmonary disease; MRC = Medical Research Council of South Africa; PCAT = Primary Care Assessment Tool; PIP = Problem Identification Program; WHO = World Health Organization. We trained 4 teams with a total of 16 fieldworkers (11 health professionals and 5 assistants with previous experience in research data collection) to collect data in the 7 provinces according to a detailed fieldwork protocol (Supplemental Appendix 4 at http://www.AnnFamMed.org/content/16/1/28/suppl/DC1). Fieldworkers were interviewed before appointment. Training was facilitated by the lead investigator (K.B.vP.) over 2 to 3 days, and consisted of face-to-face training, role playing, and practical evaluation in the field. Each team was led by a health professional and supervised by an academic family physician attached to a participating university. The teams also interacted remotely with the lead investigator (K.B.vP.) via telephone, e-mail, and a communication application (WhatsApp). Facility-level data were collected between June 2015 and March 2016, and then captured with EpiData version 3.1 (EpiData Software) via a double-entry method and using checks to minimize data entry errors.36 We then imported the data from EpiData into Microsoft Excel (Microsoft Inc) and used SPSS version 23 (IBM Corp)37 to conduct the analysis in consultation with a biostatistician. Data analysis commenced with descriptive statistics for the facilities. Subsequently, the independent samples t test for equality of means was used to compare means between the groups with and without family physicians (continuous dependent variables, see Table 2 for detail on the data collected). For those means found to be significantly different, we performed regression analysis using a generalized linear model to control for the effect of confounders. Confounding variables for health system performance were levels of staff (professional nurses, junior and senior physicians) and distance from a referral hospital. Confounding variables for clinical processes were the presence of outreach to the district health system facility (from the general specialties at the referral hospitals) and bed utilization rate (as proxy of district hospital inpatient workload). This study was approved by the Health Research Ethics Committee (Medical), Stellenbosch University (reference S15/01/003) and by each partner institution. The 7 provincial health authorities and research committees also gave permission to access facilities across the study setting (Supplemental Appendix 5 at http://www.AnnFamMed.org/content/16/1/28/suppl/DC1).

Izinto zokwakha

N/A

Emisha

Based on the provided description, it seems that the study is focused on evaluating the influence of family physicians on the South African district health system. The study found that district hospitals with family physicians generally scored better on indicators of health system performance and clinical processes, while community health centers with family physicians scored more poorly on these indicators. The study suggests that further research is needed on the influence of family physicians at the primary care level.

Based on this information, here are some potential recommendations for innovations to improve access to maternal health:

1. Increase the presence of family physicians in district hospitals: Since district hospitals with family physicians generally scored better on indicators of health system performance and clinical processes, increasing the number of family physicians in district hospitals could improve access to maternal health services.

2. Improve coordination and continuity of care in community health centers: The study found that community health centers with family physicians scored more poorly on indicators of health system performance and clinical processes, particularly in terms of continuity of care and coordination. Innovations that focus on improving coordination and continuity of care in community health centers could help improve access to maternal health services.

3. Conduct further research on the influence of family physicians at the primary care level: The study’s findings regarding community health centers were surprising and inconsistent with the global literature. Further research is needed to better understand the influence of family physicians at the primary care level and identify potential innovations to improve access to maternal health services in these settings.

4. Implement training programs for family physicians in maternal health: To enhance the impact of family physicians on maternal health, specific training programs could be developed to equip them with the necessary skills and knowledge in this area. This could help improve the quality of maternal health services provided by family physicians in both district hospitals and community health centers.

5. Strengthen collaboration between family physicians and other healthcare providers: Collaboration between family physicians and other healthcare providers, such as obstetricians, midwives, and nurses, is crucial for ensuring comprehensive and integrated maternal health care. Innovations that promote effective collaboration and communication among healthcare providers could enhance access to maternal health services.

It is important to note that these recommendations are based on the information provided in the description and may need to be further explored and tailored to the specific context and needs of the South African district health system.

AI Innovations Description

The study mentioned is titled “The influence of family physicians within the South African district health system: A cross-sectional study.” The purpose of the study was to evaluate the influence of family physicians on the South African district health system. The study compared district hospitals and community health centers with and without family physicians.

The findings of the study showed that district hospitals with family physicians generally scored better on indicators of health system performance and clinical processes. They also had fewer modifiable factors associated with pediatric mortality. However, among community health centers, those with family physicians generally scored more poorly on indicators of health system performance and clinical processes.

The study suggests that having family physicians on staff can have a positive impact on the performance and processes of district hospitals. However, the influence of family physicians at the primary care level, specifically in community health centers, was not consistent with the global literature. Further research is needed to understand the influence of family physicians at the primary care level.

Based on these findings, a recommendation to improve access to maternal health could be to prioritize the placement of family physicians in district hospitals, where their presence has shown to have a positive impact on health system performance and clinical processes. This could help ensure that pregnant women have access to quality care and reduce modifiable factors associated with maternal mortality. Additionally, further research should be conducted to understand the specific challenges and opportunities for family physicians in community health centers, in order to develop targeted strategies for improvement.

AI Innovations Methodology

The study you provided is titled “The influence of family physicians within the South African district health system: A cross-sectional study.” The purpose of the study was to evaluate the influence of family physicians on the South African district health system. The study compared district hospitals and community health centers with and without family physicians, assessing indicators of health system performance and clinical processes.

To simulate the impact of recommendations on improving access to maternal health, a methodology could be developed using the following steps:

1. Identify the recommendations: Review existing literature and consult with experts to identify potential recommendations for improving access to maternal health. These recommendations could include interventions such as increasing the number of skilled birth attendants, improving transportation infrastructure, implementing telemedicine services, or enhancing community outreach programs.

2. Define the simulation model: Develop a simulation model that represents the current state of maternal health access in the target population. This model should include relevant variables such as population demographics, healthcare facilities, healthcare providers, transportation systems, and other factors that influence access to maternal health services.

3. Incorporate the recommendations: Integrate the identified recommendations into the simulation model. This may involve adjusting variables such as the number of skilled birth attendants, the availability of transportation options, or the reach of community outreach programs.

4. Simulate the impact: Run the simulation model with the incorporated recommendations to assess their impact on improving access to maternal health. This could involve measuring indicators such as the number of women receiving prenatal care, the distance traveled to access maternal health services, or the reduction in maternal mortality rates.

5. Analyze the results: Analyze the simulation results to determine the effectiveness of the recommendations in improving access to maternal health. Compare the outcomes of the simulation with the baseline scenario to assess the magnitude of the impact.

6. Refine and iterate: Based on the analysis of the simulation results, refine the recommendations and the simulation model as needed. Iterate the simulation process to further optimize the recommendations and assess their potential long-term impact.

By following this methodology, policymakers and healthcare professionals can gain insights into the potential impact of different recommendations on improving access to maternal health. This information can inform decision-making and resource allocation to prioritize interventions that are most likely to have a positive impact on maternal health outcomes.

Umbhali

Dima Health

Statistics:

Citations: 14

Identifiers:

DOI: 10.1370/afm.2133

ISSN: 15441709

Research Areas:

Community Interventions, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Noncommunicable Diseases, Quality of Care, Social Determinants, Violence and Injury

Study Countries:

South Africa

Study Design:

Case-Control Study, Cross Sectional Study, Grounded Theory, Quasi Experimental Study, randomised-control-trial

Study Approach:

Quantitative

Yabelana ngalokhu: