“The pursuit of value for money has become the holy grail of health systems worldwide” said Professor Peter Smith. Most would agree that this is a worthy goal of interest to both payers and patients, ensuring that limited resources are used to their maximum potential and that there is no ‘waste’. In abstract terms, this is straightforward, representing the ratio of some health system output to the associated costs.
Yet, moving from the abstract concept of value for money to the concrete study of economic efficiency has proven troublesome. With health systems struggling under the weight of the Covid-19 pandemic, and faced with the prospect of tackling a backlog of non-Covid-19 patients, there can be no more critical time to solve the efficiency measurement problem in health care.
In this blog, we discuss some recent progress made by the Office of Health Economics (OHE) in tackling this issue, which may help improve the delivery of primary care services in England and beyond.
Apples and Oranges
In most sectors, goods and services are traded in markets, making it possible to measure and value the total output of a producer. In these settings, analysing efficiency is mostly trivial. In health care, this is deeply problematic because there is no common unit of output, no traded prices, no values. It is easy to be incorrectly comparing apples and oranges. For example, comparing activity levels or physical outputs – such the number of consultations provided, surgical procedures performed, or medicines prescribed – tells us nothing about the value of that output in terms of health, such as the impact on length or quality of life. In fact, the impact on the health of patients varies across different types of health care services (e.g. consultations versus surgical procedures); or the same health service may impact the health of patients differently depending on the quality standards of its delivery (e.g. right versus wrong medical prescriptions).
Valuing health care output based on the incremental health produced is, however, challenging due to the lack of routinely collected data on health outcomes (Castelli et al., 2007). As a result, the efficiency literature on health care has relied mainly on indicators of physical output.
Primary care: a land of opportunities for understanding and improving efficiency
Challenges in analysing efficiency are exacerbated in primary care. In many countries, primary care provides the first point of access to health care in case of need, coordinates patients’ care with specialists, and proactively helps individuals stay healthy throughout their lives. Due to the holistic and wide-reaching nature of its services, identifying all the relevant inputs and valued outputs in primary care is not straightforward.
Data are also a significant issue. Comprehensive data are necessary to measure the valued output associated with multiple primary care services, and to take into account the many factors outside the control of primary care that may affect its performance (e.g. patient case-mix, socio-demographic characteristics). An example of this is offered by the annual analysis of NHS productivity growth, where the total volume of primary care consultation is estimated from survey data, as opposed to sample data which guarantee greater representativeness of national-level activity. Quality instead is proxied by QOF scores on three selected conditions (coronary heart disease, stroke, hypertension).
Despite these apparent challenges, the current environment is ripe with opportunities for improving and maximising primary care efficiency.
Countries like England are experiencing pressure due to the long-term population ageing, which over time have increased the number and the complexity of primary care consultations. While the NHS in England has committed to investing additional resources in primary care and expanding its workforce, efficiency improvements are desirable to avoid that heavy demand quickly eroding this investment.
Opportunities to optimise the use of resources in England should also be explored in the context of Primary Care Networks (PCN). Introduced in 2019, PCNs are groupings of neighbouring general practices that collaborate as networks to strengthen the delivery of specific services. PCNs will employ new staffing roles (e.g. physiotherapists, community paramedics, social prescribing workers) thus offering a setting to understand substitution patterns with the traditional general practice workforce.
Further, the Covid-19 pandemic has suddenly and drastically changed the models of primary care delivery. Over the past year, most routine primary care consultations have been taking place remotely via telephone, video, or online consultations, causing a ‘shock in digitalisation’. With some of these changes likely to characterise the configuration of services well beyond the Covid-19 pandemic, we need a deeper understanding of technology’s potential to optimise the use of resources in primary care while benefitting patients equally.
A starting point
OHE has recently completed a systematic literature review of studies on primary care efficiency, as part of a multi-year study into primary care efficiency funded by The Health Foundation.
The objective of this literature review was to evaluate the suitability of existing measurement approaches to capture the quality of the multiple services offered by primary care. The review has drawn on a large evidence base including both the economic and health service literature, and studies using different methods of analysis.
Our findings resonate with the larger body of the literature on healthcare efficiency, both within and beyond primary care. Not surprisingly, one of the main limitations that we identified relates to the definition of the output. In the studies reviewed, output was typically measured using levels of primary care activity – with or without adjustments for the quality of the underlying processes, but with limited reference to the health outcomes achieved. These measures of output also differentiated crudely between different types of primary care services, or focussed on a reduced selection of them, as driven by available data. Recent studies looking at the impact of technological change on efficiency and the substitution patterns across staffing roles were also lacking.
One of the main recommendations of this study relates to the development of improved approaches to measure primary care output that are both realistic and pragmatic to implement. We do not advocate for an idealistic but unrealistic target, where data on all health outcomes achieved in primary care are routinely measured. However, we recommend renewed effort in defining intermediate health outcomes that, where possible, are amenable to primary care intervention, and that can reasonably proxy the final impact on health. A good but currently rare example of this is in diabetes care, where the level of HbA1C (intermediate outcome) in diabetic patients is used as a proxy for the probability of developing complications (final outcome). A second aim of future research should be to implement a comprehensive definition of primary care output, with sufficient differentiation across clinical areas of primary care.
The article was published on 5 August 2021. It can be accessed at this link and may be cited as Neri, M., Cubi-Molla, P. & Cookson, G. Approaches to Measure Efficiency in Primary Care: A Systematic Literature Review. Appl Health Econ Health Policy (2021). https://doi.org/10.1007/s40258-021-00669-x
Bojke, C., Castelli, A., Grasic, K., Howdon, D.D.H., Street, A.D. and Rodriguez Santana, I.D.L.N., 2017. Productivity of the English NHS: 2014/15 update.
Castelli, A., Dawson, D., Gravelle, H., Jacobs, R., Kind, P., Loveridge, P., Martin, S., O’Mahony, M., Stevens, P.A., Stokes, L. and Street, A., 2007. A new approach to measuring health system output and productivity. National Institute Economic Review, 200(1), pp.105-117.
Fisher, R., Thorlby, R. and Alderwick, H., 2019. Understanding primary care networks. https://www.health.org.uk/publications/reports/understanding-primary-care-networks
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Sandall, J., Murrells, T., Dodwell, M., Gibson, R., Bewley, S., Coxon, K., Bick, D., Cookson, G., Warwick, C. and Hamilton-Fairley, D., 2014. The efficient use of the maternity workforce and the implications for safety and quality in maternity care: a population-based, cross-sectional study. Health Services and Delivery Research, No. 2.38. DOI.
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