Avoidable hospital admissions
Strengthening primary healthcare is one of the most effective interventions for improving healthcare systems efficiency and population health. Functions of the primary level of care include health promotion and disease prevention, serve as the first point of contact for managing new non-emergency health issues, and referring patients to specialist care and hospital-based services when appropriate. A high-performing primary care system that provides accessible and high-quality services can reduce acute deterioration in people living with four long-term conditions that are widely prevalent in LAC; asthma, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), high blood pressure and diabetes, and reduce unnecessary admissions to hospital. For this reason, measuring the number of hospitalisations with these diseases as the main diagnosis is and indicator of the capacities of the healthcare system to provide necessary care at an early stage in the primary level. Because of the postponement of non-emergency services in 2020 due to the COVID-19 pandemic, hospitalisation rates in 2021 might include the effect of countries’ efforts to clear the backlog of services and not purely reflect the quality of the health system to minimise avoidable hospitalisations. In this line, figures should be interpreted with caution.
Figure 7.11 shows hospital admission rates per 100 000 population for asthma and COPD for six LAC countries with available data. All LAC6 countries present lower hospitalisations rates than the OECD average (32.2 for Asthma and 151.2 for COPD). Peru presents the lowest hospitalisation rates for these conditions with 1.6 and 0.8 for asthma and COPD per 100 000 population, respectively. Further, public health mandates related to COVID-19, such as physical distancing and facemask use, can have an influence in hospitalisation rates for asthma and COPD (Alqahtani et al., 2021[1]).
Figure 7.12 shows admission rates for CHF and hypertension. As with asthma and COPD, the graph reveals that the reporting LAC6 countries have lower rates than the OECD average. Costa Rica reports the lowest rate for both conditions-related admissions per 100 000 population, just 5 for CHF, and 6 for hypertension.
Figure 7.13 displays admission rates for diabetes. Chile (92), Costa Rica (104) and Brazil (120) report admission rates closer to the OECD average (119), while Mexico’s is higher at 208 admissions per 100 000 population. Colombia and Peru stand below the OECD average at 55 and 26 admissions respectively.
Figures presented in this section suggest that six LAC countries have been successful at minimising avoidable admissions. However, the stark differences with the OECD average makes it important to consider the possibility that the differences in access to healthcare drive a certain degree of underutilisation of hospital resources. Health systems must find an adequate balance to ensure the least wasteful level of hospital utilisation while ensuring adequate access across the entire population. LAC countries must continue to invest in building primary care capacity in order to minimise waste and prepare for a heavier burden caused by the increased prevalence of chronic conditions brought on by the population ageing phenomena observed in LAC (see Chapter 9).
The indicators are defined as the number of hospital admissions with a primary diagnosis of asthma, COPD, CHF, hypertension and diabetes among people aged 15 years and over per 100 000 population. Rates are age-sex standardised to the 2010 OECD population aged 15 and over. Admissions resulting from a transfer from another hospital and where the patient dies during the admission are excluded from the calculation as these admissions are considered unlikely to be avoidable. Disease prevalence and availability of hospital care may explain some, not all, variations in cross-country rates. Differences in coding practices among countries may also affect the comparability of data. For example, the exclusion of “transfers” cannot be fully complied with by some countries. Differences in data coverage of the national hospital sector across countries may also influence indicator rates. Differences in coding practices across countries must be considered as a possible source of bias, for instance, in the case of hypertension.
References
[1] Kielbassa, A. (ed.) (2021), “Reduction in hospitalised COPD exacerbations during COVID-19: A systematic review and meta-analysis”, PLOS ONE, Vol. 16/8, p. e0255659, https://doi.org/10.1371/journal.pone.0255659.
Source: OECD Health Statistics 2021 and Ministries of Health of Brazil, Colombia and Peru.
Source: OECD Health Statistics 2022.
Source: OECD Health Statistics 2022 and national data sources.