Potentially Inappropriate Prescribing (PIP) in Long-Term Care (LTC) Patients

Potentially Inappropriate Prescribing (PIP) in Long-Term Care (LTC) Patients: Validation of the 2014 STOPP-START and 2012 Beers Criteria in a LTC Population

The study objectives are: to validate the subsets of Screening Tool of Older People's Prescriptions (STOPP) and Screening Tool to Alert Right Treatment (START), or STOPP/START criteria, and Beers criteria applicable to HAD by comparing their performance when applied to clinical and HAD for the same patients, and, using clinical data, to compare the performance of the full STOPP/START and full Beers criteria with each other.

Potentially inappropriate prescribing (PIP) is frequent, particularly in Long-Term Care (LTC) patients. Tools such as STOPP/START and Beers criteria were developed to identify PIP in clinical settings. Due to lack of clinical data in such databases, only a subset of these criteria are applicable to routinely collected health administrative data (HAD). This subset was shown to identify PIP in HAD with a frequency comparable to clinical studies using the full STOPP-START criteria. Nonetheless, the performance of subsets of STOPP/START and Beers criteria in HAD compared to clinical data from the same patients is unknown; furthermore, the performance of the updated 2014 STOPP-START and 2012 Beers criteria compared with one another is also unknown.

The overall aim of this study is to validate medication appropriateness criteria applicable to HAD by comparing their performance when applied to clinical data. The present study has two main and three secondary objectives (see Figure 1 for details):

A. Main objectives:

Objective 1: To validate subsets of the STOPP/START and Beers criteria defined by their applicability to HAD, by comparing their performance in detecting PIP when applied to HAD with that of the full set of criteria applied to clinical data for the same residents (with the clinical data providing the "gold standard").

Objective 2: To compare the detection rates of the full STOPP/START and full Beers criteria with one another when applied to clinical data.

B. Secondary objectives:

Objective 3: To assess the number and proportion of unidentified PIP when using the subset of STOPP/START and Beers criteria with HAD when compared with the full set of criteria, when applied to clinical data.

Objective 4: To compare the performance of the subset of the STOPP/START and Beers criteria applied to the HAD in detecting PIP when compared to clinical data for the same residents.

Objective 5: To compare the performance of the subset of STOPP/START and Beers criteria applicable to HAD with one another when applied to HAD.

To achieve these objectives, the investigators will conduct a cross-sectional study of linked HAD and clinical data. Eligible patients will be 66 years and over and recently admitted to one of six LTC facilities in Ottawa, Ontario, beginning June 1st, 2014. The target sample size is 275, but recruitment may stop if interim analyses demonstrate statistical significance can be achieved with fewer patients. Medication, diagnostic and clinical data will be collected after admission by a pharmacist not otherwise involved in the patient's care. The main outcome measure is the proportion of PIP missed by the subset of STOPP/START criteria applied to HAD when compared to clinical data (the gold standard).

Inclusion Criteria:

• OHIP-eligible resident aged 66 and over at the time of admission to long-term care in Ottawa
• Newly admitted to LTC or convalescent care at the participating care facilities
• Consent to participate

Exclusion Criteria:

• Residents will be excluded if they decline to participate in the study.
• Residents will be excluded if they do not have a valid Ontario Health Insurance Plan (OHIP) number.
• Residents residing in Ontario whose health care is covered through other plans, and are therefore not captured through ICES data, such as First Nations people living on reserve, members of the Armed Forces, and refugee claimants, will also be excluded.
• A resident will also be excluded if he or she has no prescribed medications.