Principal findings
There was a high prevalence of PIP in those aged ≥70 years in Ireland in 2007 and nearly all GPs had at least one patient with PIP. The most prevalent PIP drugs were PPIs at maximum therapeutic dosage for >8 weeks, followed by NSAIDs for >3 months and long-acting benzodiazepines for >1 month. The National Institute for Health and Clinical Excellence (NICE) guidelines recommend regular review of patients to assess their continuing need for PPIs and the use of step-down therapy [
20]. Long-term PPI treatment has significant cost consequences [
21,
22]. NSAID use is associated with gastrointestinal adverse effects and hospitalisation and long-acting benzodiazepines are associated with an increased risk of falls, fractures, impaired cognition and dependence problems in older populations [
23,
24]. Drug duplication on the same prescription claim was also prevalent and concurrent use of NSAIDs has been shown to increase the risk of gastrointestinal toxicity [
25].
The individual STOPP indicators can be used with reasonable confidence to identify GPs as having above or below average proportions of PIP (average > 0.8 reliability for 90% of GPs). Although the composite indicator had lower reliability, it is likely in practice that the individual indicators would be used to monitor the quality of prescribing. There is also evidence that the STOPP criteria have predictive validity with an association found between STOPP and ADEs in older hospitalised patients [
26].
There was relatively little variation in PIP between GPs in Ireland at the GP level, the majority of the variation was at the patient level. While there was evidence of significant variation in PIP between GPs in the unadjusted analysis (Figure
1) after adjustment for patient level variables the majority of this remaining variation was no longer significant (Figure
2). This remaining variation (significant and non-significant) was not explained by adding GP level variables to the model. The characteristics of the GPs did not substantively affect the likelihood of receiving a PIP indicator at the patient level. The multilevel logistic regression model for the STOPP composite indicator found that only the number of different repeat drug classes was strongly associated with the likelihood of receiving a potentially inappropriate indicator. Other patient and GP level variables were found to be significantly associated with PIP but their odds ratios were close to one in the adjusted multilevel models. The association between the number of different repeat drug classes and the likelihood of receiving a potentially inappropriate indicator varied across GPs; the lower or higher the number of repeat drug classes the more variability in PIP between GPs.
A recent Scottish study investigated the variation in PIP between 315 practices and 139,404 patients defined as vulnerable to ADEs using 15 indicators based on explicit national prescribing safety advice (median 12.5%, IQR, 10.1%, 15.3%) [
7]. Unlike the current study, the variation between practices was considerable even after adjusting for patient case mix and practice characteristics. Practices which were statistically different from average varied from having half (-50%) the expected rates of PIP prescribing to having 50%-125% in excess. The MOR was higher than the current study (1.42, 95% CI, 1.37, 1.47) [
7]. The study populations and prevalence of PIP were different for the two studies which may explain the differences in variation between prescribers [
7]. Both studies did however identify considerable unexplained significant and non-significant variation in PIP between prescribers and found that practice level variables did not account for this variation (additional 0.5% in both studies); only the patient level factor number of drug classes was strongly associated with PIP [
7].
This study has identified that reductions in PIP will require improvement across all GPs to reduce the average rate of PIP rather than focusing on a few select GPs (outliers). The number of different repeat medications has consistently been shown to be an independent predictor for PIP in numerous studies [
7,
14,
27‐
29]. The prescription of multiple medications in older adults has also been associated with an increased risk of drug interactions, adherence problems, ADEs and drug costs [
27,
30]. There is some evidence that interventions targeting polypharmacy in older people, using pharmaceutical care or computerised decision support, are successful in reducing medication related problems such as PIP. These and other forms of interventions that help the prescriber modify or reduce PIP in older patients should be developed and evaluated in randomised controlled trials [
30].
Strengths and limitations
This study has a number of limitations. The lack of diagnostic information in the database limited the applicability of all of the STOPP criteria and the investigation of individual patient factors and differences in drug indication. It is likely that estimates of PIP and comparisons across GPs are conservative. [
31] There was a possibility of confounding by indication and patient case mix when comparing PIP rates across different GPs. However, the variable number of different repeat drug classes should account for most of the unmeasured variability in patient co-morbidities between GPs.
There was a small proportion of patients (3.5%) who were assigned to more than one GP in 2007 and these patients were assigned to the GP who prescribed their medication on a consistent basis, or their most recent GP if more than one GP prescribed their medication on a consistent basis. Therefore, a certain proportion of prescribing is unaccounted for in the analysis which may result in a more conservative estimate of PIP. In addition, the database does not include OTC items, although this is not likely to be a significant factor as the scheme provides free medical treatment and patients must pay for OTC items.
The multilevel approach used in this study controlled for confounding by including both patient and GP level predictors of PIP. In general GP variation in prescribing reflects different therapeutic approaches to health problems in older populations but the current study found minimum variation in PIP between GPs. Also none of the available patient and GP level factors could explain the remaining variation in PIP between GPs. The database had a limited number of GP and patient variables, hence limiting the ability to explain all of the remaining variance. Further multilevel research is required to investigate and understand which factors influence PIP at the different levels of health care organisation; patient, GP, and practice organisation and culture [
7,
32].
Notwithstanding the limitations, this study is one of the first studies to examine how PIP varies between both patients and GPs in a national older population [
7]. The application of PIP indicators to prescription databases at the patient, GP and practice level provides useful information for assessing and comparing prescribing at the population level [
33].
Policy implications
The development of PIP guidelines and their implementation is expensive and must bring value in terms of improved prescribing quality and patient outcomes. Studies on the effectiveness of clinical guidelines have been conflicting but they are effective if well constructed and implemented consistently. Guidelines also need to be closely monitored and prescribers educated to comply with them [
34‐
36]. The introduction of regulatory prescribing guidelines were poorly followed in France because of the volume, lack of information systems and limited capacity for monitoring [
37]. While in the UK, education on the use of guidelines on prescribing nutritional supplements significantly reduced total prescribing by 15% and inappropriate prescribing from 77% to 59% [
38]. The use of computerised clinical decision support, academic detailing and pharmacist intervention has had some success in reducing PIP and further research on their implementation is required [
39‐
42].
There is also evidence that guidelines are effective if accompanied by pay for performance financial incentives [
43]. Performance measurements do offer an efficient mechanism to regulate health care providers, increase accountability and encourage quality improvement and care but can alienate providers and make them obstinate to change [
44‐
46]. Not all PIP measured in prescribing databases may be inappropriate and screening tools will never be substitutes for clinical assessment and judgment. However they can be used to identify high rates of PIP and monitor and improve prescribing practices in older populations.