Many frail elderly individuals use several medications, which can lead to unnecessary adverse drug events, resulting in medication-associated hospitalizations of which up to half are potentially preventable .
Several methods are available to improve the appropriateness of medications used by the elderly. For example, the Prescribing Optimization Method (POM)  evaluates medication adherence and classifies potentially inappropriate prescriptions into different categories. As most clinical specialists do not have a complete overview of all the medicines prescribed or used by patients and often do not have sufficient time or knowledge to optimize polypharmacy, it can be expected that the number of physicians visited contributes to inappropriate prescribing. Previous studies have shown that inappropriate prescribing is associated with multiple prescribers [3-5].
The objective of our cross-sectional study was to investigate the relationship between the number of physicians visited and inappropriate prescribing in geriatric patients in the Netherlands.
One of the authors (RV) quantified the original POM questions into the domains to form an index (sumPOM) (see Table 1) to evaluate whether the medications used by elderly patients on admission to an acute geriatric ward of a teaching hospital in Tilburg, the Netherlands had been prescribed inappropriately. Under-prescription (scored 1 point) was assessed in each patient and each drug was evaluated in terms of the remaining seven domains. If a drug was prescribed without its indication being clearly stated, then it was not evaluated for lack of effect. Prophylactic medications were considered effective. Per drug, each domain was scored 0 points if it was appropriate and 1 point if it was inappropriate. The causality of adverse effects was determined with the Naranjo scale.
|Domain||Score 0 point||Score 1 point|
|Lack of indication||Absent or uncertain||Present|
|Lack of effect||Absent or uncertain||Present|
|Improper dose in relation to renal function*||Absent||Present|
|Potential clinically relevant drug–drug interactions*||Absent||Present|
|Potential clinically relevant drug–disease interactions*||Absent||Present|
|Adverse effect||According to Naranjo criteria unlikely||According to Naranjo criteria at least possible|
|Option to reduce dose frequency||Not possible (or already performed)||Possible (or not already performed)|
Two hundred patients [mean age 82.8 (± 6.4 = SD) years] had a mean of 8.6 (± 4.2) prescriptions and had visited a mean of 3.3 (± 1.7) different physicians in the year before admission. The sumPOM score ranged from 0 to 20. In each patient there were 5 (± 3.8) instances of inappropriate prescribing, involving all classes of drugs. The number of physicians visited was clearly associated with inappropriate prescribing on univariate regression analysis [regression coefficient (β) 0.54, 95% CI 0.24, 0.84] (Table 2), but not after adjustment for the number of prescriptions (β −0.02, 95% CI −0.28, 0.24). The number of physicians visited was also related to the number of prescriptions (β 0.82, 95% CI 0.48, 1.15) (data not shown). The number of prescriptions remained the most important independent predictor of inappropriate prescribing in the full model multivariate regression analysis (β 0.52, 95% CI 0.40, 0.64). In this model, living in warden-assisted or sheltered accommodation was associated with a higher rate of inappropriate prescribing than living independently (β 1.91, 95% CI 0.31, 3.51). In contrast, previous contact with a geriatrician was a significant predictor of fewer inappropriate medications (β −1.32, 95% CI −2.29, 0.35), probably because geriatricians are more aware of potential medication-related problems in elderly patients.
|Variable||Univariate||Univariate with adjustment for the number of prescriptions||Multivariate Full model|
|Regression coefficient||95% CI||Regression coefficient||95% CI||Regression coefficient||95% CI|
|Number of visited physicians in the previous year||0.54||0.24, 0.84||−0.02||−0.28, 0.24||0.20||−0.09, 0.50|
|Contact with a geriatrician in the previous year||−0.84||−1.96, 0.01||−0.83||−1.70, 0.05||−1.32||−2.29, −0.35|
|Number of prescriptions||0.56||0.46, 0.66||–||–||0.52||0.40, 0.64|
|eGFR||−0.02||−0.04, 0.01||−0.02||−0.03, 0.002||−0.02||−0.04, 0.01|
|Age||−0.01||−0.09, 0.07||0.05||−0.02, 0.11||−0.01||−0.10, 0.08|
|Charlson index||0.29||0.05, 0.53||0.10||−0.10, 0.29||−0.003||−0.23, 0.23|
|Male||−1.08||−2.16, −0.01||−0.27||−1.12, 0.59||−0.05||−1.01, 0.91|
|Unmarried||−0.71||−0.41, 1.82||−0.35||−1.22, 0.53||−0.20||−1.23, 0.83|
|Married||−2.31||−4.09, −0.53||−1.53||−2.93, −0.13||−1.49||−3.00, 0.02|
|Not impaired||0.07||−1.06, 1.20||−0.74||−1.63, 0.15||−0.67||−1.60, 0.27|
|Living in a nursing home||3.15||0.95, 5.34||−0.36||−1.90, 1.82||−0.12||−2.08, 1.85|
|Living in a residential home||2.05||0.67, 3.44||−0.71||−0.43, 1.85||0.59||−0.67, 1.85|
|Living in warden-assisted/sheltered accommodation||3.27||1.38, 5.16||1.87||0.33, 3.41||1.91||0.31, 3.51|
|Supportive care at home||1.08||−0.23, 2.40||0.65||−0.41, 1.70||0.70||−0.40, 1.80|
In a further analysis (data not shown), individual POM domains were not independently associated with the number of physicians visited.
The sumPOM collects information about implicit inappropriate prescribing (whether a drug was indicated), but also about explicit inappropriate prescribing (potential drug–drug and drug–disease interactions). Both may adversely affect the benefit : harm ratio of treatment. We did not investigate the clinical consequences of inappropriate prescribing, but it is known that they are associated with preventable harm .
In conclusion, many elderly patients admitted to an acute geriatric ward had been prescribed inappropriate medications. However, a visit to a geriatrician in the previous year was found to be associated with fewer inappropriate prescriptions. Physicians' prescribing skills, especially regarding polypharmacy, can be improved by using a systematic medication review method, such as the POM. Like others [3-5], we found the number of physicians visited to be associated with inappropriate prescribing on univariate analysis, but not after adjustment for the number of prescriptions. This makes it important to adjust for the number of drugs used in future studies of risk factors for inappropriate prescribing.