The prevalence of sub-optimal monitoring was high in this population of community-dwelling older adults in Irish primary care. Almost 80% of individuals prescribed one of the included higher-risk drugs had ≥1 unmonitored monthly dispensing over the 5-year study period, and almost 24% of all dispensings of included higher-risk drugs were unmonitored. The generalisability of this finding may be limited given the unique context of Irish primary care during the study period, where the management of chronic disease in the community was unfunded and unstructured. Participants prescribed one of the higher-risk drugs of interest were significantly older, took more medicines and experienced higher levels of socioeconomic deprivation. This is unsurprising considering the strong link between socioeconomic deprivation and multimorbidity.1

Patient characteristics associated with sub-optimal monitoring included the number of drugs, socioeconomic deprivation and anxiety/depression symptoms, with the largest effect seen for anxiety/depression symptoms indicating that these patients are at potentially at higher risk for preventable drug related harm.

Our study identified that baseline sub-optimal monitoring was associated with significant increased odds of having an emergency department visit at follow-up. However, the effect size was small, there was no evidence of an association with unplanned hospital admission and the findings are also subject to the influence of potential unmeasured confounders. It is also important to bear in mind that there are inconsistencies across guidelines on optimal monitoring intervals and there is growing recognition that many of these recommendations may be low value or yield and add to an often high level of disease and treatment burden for patients with multimorbidity.20 21

This study adds to the limited literature in the area of laboratory monitoring of higher risk medicines in primary care. A major strength of this study is the inclusion of patient reported outcome measures, and we identified anxiety/depression as a significant predictor of sub-optimal monitoring of higher-risk medicines. Due to the wide variation in the levels of laboratory monitoring, various sensitivity analyses were conducted to further explore the results, and this is another strength of this work. A sub-group analysis was conducted examining the predictors of sub-optimal monitoring limited to participants with high levels of sub-optimal monitoring, and a second analysis was conducted where the number of unmonitored dispensings was truncated due to the long tailed distribution of the variable. Similar results were returned for both models indicating that are results are not being driven by either extreme ends of the spectrum.

The main limitation is the context in which the study was conducted, which has changed over time. There has been markedly increased uptake in the use of electronic communications between primary and secondary care over the past 10 years; however, in 2010, most general practices in Ireland received laboratory results in paper format and scanned to the patient’s electronic record. It is possible that delays and errors in this process affected the quality of data and over-estimated the prevalence of sub-optimal monitoring. Recent improvements in both healthcare technology and the delivery of chronic disease management programmes may mean that the laboratory monitoring practices observed during the study period may not reflect the current landscape. In addition, for this study, we assessed the number of days between dispensing and the relevant laboratory monitoring. We did not assess the outcome of laboratory monitoring. A recent study based in UK primary care indicated that only a quarter of individuals having laboratory blood tests had completely normal results, yet only 48% of tests resulted in any change in management.22 Finally, older people with multiple chronic illness often attend multiple hospital outpatient clinics. It is likely many of these patients had either some or all of their monitoring in secondary care, and although we did include secondary care results where available in the GP electronic health record it is likely that this was not fully captured.

A systematic review of the incidence and characteristics of preventable adverse drug events in ambulatory care identified inadequate monitoring (45.4%; range 22.2–69.8%) as the most frequent error of omission that resulted in hospital admission.23 The prevalence of sub-optimal monitoring was higher in our study, compared with similar studies in the USA and UK.3 24–26 However, these studies included the entire primary care population, and our study included older adults aged ≥70 years. Notwithstanding the different population under investigation, the difference in the prevalence of monitoring was substantial. For example, a recent analysis assessing the implementation of the PINCER indicators in the UK reported that 5% of patients prescribed loop diuretics or angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor blockers (ARBs) had sub-optimal monitoring compared 34% in this study.24 Despite the lower prevalence of sub-optimal monitoring, the relative prevalence of monitoring across included indicators is similar to other studies, with lower adherence for amiodarone and methotrexate monitoring.24 Similar factors associated with sub-optimal monitoring such as deprivation and increased number of drugs have been found in other studies.3 26 Anxiety/depression was identified as a significant predictor of sub-optimal monitoring, and no other study including patient-reported outcome measures could be identified for comparison. There is no clear evidence of the impact of sub-optimal monitoring on patient outcomes. In this study, there was no evidence of an association between sub-optimal monitoring and unplanned hospital admissions, but there was a small but significantly increased odds of emergency department visits. The reverse relationship with healthcare usage has been also been reported, whereby higher rates of monitoring were associated with a small but significantly increased rate of unplanned hospital admissions.26 In our population, monitored participants had a significantly higher proportion of unplanned hospital admissions at baseline, compared with participants who were fully monitored. These results reflect the multiple factors at play, whereby patients who have had a recent hospital admission may be more likely to have laboratory blood tests after discharge.

There is evidence that well-developed primary care systems are associated with improved outcomes for patients and a more equitable distribution of healthcare.27–29 As recently as 2018, Ireland was far below European averages with respect to the proportion of the health budget spent on primary care (<5%),30 and this study was set in that context. There have been recent improvements, notably with the introduction of a funded structured Chronic Disease Management programme, where GPs are reimbursed to provide two structured patient visits per year including blood monitoring for specific chronic medical conditions. The results from this study will be an important benchmark for future changes.

Although there were some limitations with respect to our estimates of sub-optimal monitoring in this population, there was significant variation in the prevalence of laboratory testing at both the individual and practice level (online supplemental appendix 2). A comparative analysis of laboratory requesting patterns across 22 general practices in a single district in the UK concluded that the large differences observed in laboratory testing probably result from individual variation in clinical practice.31 In our analysis which included people aged ≥70 years and prescribed ≥1 medicine, we found that increasing age and reduced functional ability were both associated with less frequent renal blood testing. These results may indicate some unmet need in this population.

Our study attempted to quantify the prevalence of necessary testing with respect to monitoring of higher-risk prescriptions, but consideration also needs to be given to unnecessary testing and the impact this may have on resource allocation. Attempting to define unnecessary testing is complex however, with qualitative work suggesting that laboratory testing is sometimes used as a way to be seen to be doing something in the context of patient expectations and as a means for managing diagnostic uncertainty.32 A retrospective cohort study based in the USA that explored suboptimal monitoring of ACEI and ARBs found that higher-risk individuals, such as those with increasing age, multimorbidity and additional risk factors, were more likely to receive appropriate monitoring.33 This finding is particularly interesting given that monitoring intervals are often based on expert consensus rather than individual risk. It raises questions about the potential for over-monitoring in lower-risk individuals, which could represent an inefficient use of healthcare resources and increase the likelihood of detecting spurious results. Over the past 10 years, various campaigns such as the BMJ’s Too Much Medicine and American Board of Internal Medicine’s Choosing Widely Campaign have highlighted the risks of over-testing both at an individual level and due to the opportunity cost of diverting limited healthcare resources.34 35 This is particularly relevant in primary care where there are increasing concerns about managing demand and workload including increased blood testing.21 These findings highlight the complexity of laboratory monitoring, especially when balancing the need for safety with the appropriate allocation of resources. Clinicians and researchers should work to develop systems and protocols for laboratory testing to minimise unnecessary testing but capture those most likely to benefit. With respect to monitoring of higher-risk prescriptions, using computerised clinical decision support inbuilt into practice software is one potential approach.

Uncertainties around responsibility for monitoring for higher risk medicines are likely to contribute to risk and the environmental context, including the organisation of care, and have been identified as important components to managing prescribing.36 Although it is possible that many of these patients had monitoring in secondary care, this was not clear from the patient record, and this finding strengthens the argument for a shared care record to increase visibility of completed monitoring across primary and secondary care.

This analysis identified an association between baseline anxiety/depression symptoms and sub-optimal laboratory monitoring. It has been estimated that mental illness almost doubles the risk of any preventable harm in patients presenting to either primary care or the emergency department.37 It is thus important to screen for comorbid mental illness in older patients, particularly those with multimorbidity to capture this particularly vulnerable population.38

A final consideration is that the monitoring indicators included in this study were developed by expert consensus, and there may be differing opinions as to what constitutes an appropriate monitoring interval and whether a prolonged interval is likely to have significant clinical consequences.39 In this study, sub-optimal monitoring was associated with a small but significant increased odds of an emergency department visit, but there was no evidence of an effect on ADRs, mortality or unplanned admissions, and we may have been underpowered to see an effect. More research is needed to examine the optimal timing of laboratory monitoring for higher-risk medicines and the impact of sub-optimal monitoring of higher risk medicines prescribed in primary care on important clinical endpoints such as unplanned hospital admissions and ADRs. With respect to implementation, future approaches to tackle sub-optimal monitoring may include exploring the effect of shared care electronic health records and technology enabled clinical decision support systems.

In conclusion, the prevalence of sub-optimal monitoring in this population of community-dwelling older adults was high over a 5-year period. This was in the context of a primary care system without a funded chronic disease management programme. There was an association between number of drugs, deprivation, anxiety/depression and sub-optimal monitoring. Adequate resourcing and organisation of chronic disease management in primary care, as well as limiting low-value or unnecessary testing, is vital to ensure those in most need receive appropriate care. These findings may prove an important benchmark for assessing current and future laboratory monitoring requirements for higher-risk medicines in primary care.