Measuring the geographic disparity of comorbidity in commercially insured individuals compared to the distribution of physicians in South Africa.

BACKGROUND: Measuring and addressing the disparity between access to healthcare resources and underlying health needs of populations is a prominent focus in health policy development. More recently, the fair distribution of healthcare resources among population subgroups have become an important indication of health inequities. Single disease outcomes are commonly used for healthcare resource allocations; however, leveraging population-level comorbidity measures for health disparity research has been limited. This study compares the geographical distribution of comorbidity and associated healthcare utilization among commercially insured individuals in South Africa (SA) relative to the distribution of physicians. METHODS: A retrospective, cross-sectional analysis was performed comparing the geographical distribution of comorbidity and physicians for 2.6 million commercially insured individuals over 2016-2017, stratified by geographical districts and population groups in SA. We applied the Johns Hopkins ACG® System across the claims data of a large health plan administrator to measure a comorbidity risk score for each individual. By aggregating individual scores, we determined the average healthcare resource need of individuals per district, known as the comorbidity index (CMI), to describe the disease burden per district. Linear regression models were constructed to test the relationship between CMI, age, gender, population group, and population density against physician density. RESULTS: Our results showed a tendency for physicians to practice in geographic areas with more insurance enrollees and not necessarily where disease burden may be highest. This was confirmed by a negative relationship between physician density and CMI for the overall population and for three of the four major population groups. Among the population groups, the Black African population had, on average, access to fewer physicians per capita than other population groups, before and after adjusting for confounding factors. CONCLUSION: CMI is a novel measure for healthcare disparities research that considers both acute and chronic conditions contributing to current and future healthcare costs. Our study linked and compared the population-level geographical distribution of CMI to the distribution of physicians using routinely collected data. Our results could provide vital information towards the more equitable distribution of healthcare providers across population groups in SA, and to meet the healthcare needs of disadvantaged communities.

Multinational primary health care experiences from the initial wave of the COVID-19 pandemic: A qualitative analysis.

OBJECTIVE: To learn from primary health care experts' experiences from the COVID-19 pandemic across countries. METHODS: We applied qualitative thematic analysis to open-text responses from a multinational rapid response survey of primary health care experts assessing response to the initial wave of the COVID-19 pandemic. RESULTS: Respondents' comments focused on three main areas of primary health care response directly influenced by the pandemic: 1) impact on the primary care workforce, including task-shifting responsibilities outside clinician specialty and changes in scope of work, financial strains on practices, and the daily uncertainties and stress of a constantly evolving situation; 2) impact on patient care delivery, both essential care for COVID-19 cases and the non-essential care that was neglected or postponed; 3) and the shift to using new technologies. CONCLUSIONS: Primary health care experiences with the COVID-19 pandemic across the globe were similar in their levels of workforce stress, rapid technologic adaptation, and need to pivot delivery strategies, often at the expense of routine care.

Integrating primary care and public health to enhance response to a pandemic.

Primary health care (PHC) includes both primary care (PC) and essential public health (PH) functions. While much is written about the need to coordinate these two aspects, successful integration remains elusive in many countries. Furthermore, the current global pandemic has highlighted many gaps in a well-integrated PHC approach. Four key actions have been recognized as important for effective integration.A survey of PC stakeholders (clinicians, researchers, and policy-makers) from 111 countries revealed many of the challenges encountered when facing the pandemic without a coordinated effort between PC and PH functions. Participants' responses to open-ended questions underscored how each of the key actions could have been strengthened in their country and are potential factors to why a strong PC system may not have contributed to reduced mortality.By integrating PC and PH greater capacity to respond to emergencies may be possible if the synergies gained by harmonizing the two are realized.

Primary care perspectives on pandemic politics.

While the COVID-19 pandemic now affects the entire world, countries have had diverse responses. Some responded faster than others, with considerable variations in strategy. After securing border control, primary health care approaches (public health and primary care) attempt to mitigate spread through public education to reduce person-to-person contact (hygiene and physical distancing measures, lockdown procedures), triaging of cases by severity, COVID-19 testing, and contact-tracing. An international survey of primary care experts' perspectives about their country's national responseswas conducted April to early May 2020. This mixed method paper reports on whether they perceived that their country's decision-making and pandemic response was primarily driven by medical facts, economic models, or political ideals; initially intended to develop herd immunity or flatten the curve, and the level of decision-making authority (federal, state, regional). Correlations with country-level death rates and implications of political forces and processes in shaping a country's pandemic response are presented and discussed, informed by our data and by the literature. The intersection of political decision-making, public health/primary care policies and economic strategies is analysed to explore implications of COVID-19's impact on countries with different levels of social and economic development.

Assessing the geographical distribution of comorbidity among commercially insured individuals in South Africa.

BACKGROUND: Comorbidities are strong predictors of current and future healthcare needs and costs; however, comorbidities are not evenly distributed geographically. A growing need has emerged for comorbidity surveillance that can inform decision-making. Comorbidity-derived risk scores are increasingly being used as valuable measures of individual health to describe and explain disease burden in populations. METHODS: This study assessed the geographical distribution of comorbidity and its associated financial implications among commercially insured individuals in South Africa (SA). A retrospective, cross-sectional analysis was performed comparing the geographical distribution of comorbidities for 2.6 million commercially insured individuals over 2016-2017, stratified by geographical districts in SA. We applied the Johns Hopkins ACG® System across the insurance claims data of a large health plan administrator in SA to measure comorbidity as a risk score for each individual. We aggregated individual risk scores to determine the average risk score per district, also known as the comorbidity index (CMI), to describe the overall disease burden of each district. RESULTS: We observed consistently high CMI scores in districts of the Free State and KwaZulu-Natal provinces for all population groups before and after age adjustment. Some areas exhibited almost 30% higher healthcare utilization after age adjustment. Districts in the Northern Cape and Limpopo provinces had the lowest CMI scores with 40% lower than expected healthcare utilization in some areas after age adjustment. CONCLUSIONS: Our results show underlying disparities in CMI at national, provincial, and district levels. Use of geo-level CMI scores, along with other social data affecting health outcomes, can enable public health departments to improve the management of disease burdens locally and nationally. Our results could also improve the identification of underserved individuals, hence bridging the gap between public health and population health management efforts.

Relationship between the perceived strength of countries' primary care system and COVID-19 mortality: an international survey study.

BACKGROUND: Strong primary health care (PHC) is the cornerstone for universal health coverage and a country's health emergency response. PHC includes public health and first-contact primary care (PC). Internationally, the spread of COVID-19 and mortality rates vary widely. The authors hypothesised that countries perceived to have strong PHC have lower COVID-19 mortality rates. AIM: To compare perceptions of PC experts on PC system strength, pandemic preparedness, and response with COVID-19 mortality rates in countries globally. DESIGN & SETTING: A convenience sample of international PHC experts (clinicians, researchers, and policymakers) completed an online survey (in English or Spanish) on country-level PC attributes and pandemic responses. METHOD: Analyses of perceived PC strength, pandemic plan use, border controls, movement restriction, and testing against COVID-19 mortality were undertaken for 38 countries with ≥5 responses. RESULTS: In total, 1035 responses were received from 111 countries, with 1 to 163 responders per country. The 38 countries with ≥5 responses were included in the analyses. All world regions and economic tiers were represented. No correlation was found between PC strength and mortality. Country-level mortality negatively correlated with perceived stringent border control, movement restriction, and testing regimes. CONCLUSION: Countries perceived by expert participants as having a prepared pandemic plan and a strong PC system did not necessarily experience lower COVID-19 mortality rates. What appears to make a difference to containment is if and when the plan is implemented, and how PHC is mobilised to respond. Many factors contribute to spread and outcomes. Important responses are first to limit COVID-19 entry across borders, then to mobilise PHC, integrating the public health and PC sectors to mitigate spread and reduce burden on hospitals through hygiene, physical distancing, testing, triaging, and contract-tracing measures.