MedPath

The PIP-STOPP Study

Conditions
Potentially Inappropriate Prescribing (PIP)
Registration Number
NCT02555891
Lead Sponsor
Bruyere Research Institute
Brief Summary

The overall objective of the present study will be to describe the occurrence of Potentially Inappropriate Prescribing (PIP) in Ontario's elderly (\>65 yrs) population, assess the health and economic burden associated with it, and evaluate interventions aimed at mitigating its effects.

To attain this objective, the investigators will test three specific hypotheses:

Hypothesis 1: Instances of Potentially Inappropriate Prescribing are frequent and costly. To test this hypothesis, the investigators will apply a subset of the STOPP criteria and Beers criteria to Ontario health administrative data to identify instances of potentially inappropriate prescribing, and estimate potential savings, both direct and indirect, that could be achieved by reducing inappropriate prescribing.

Hypothesis 2: ED visits and hospitalizations are significantly associated with Potentially Inappropriate Prescribing. To test this hypothesis, the investigators will estimate the attributable fraction of ER visits and hospitalizations associated with different frequencies of PIP using multivariate methods and survival analysis.

Hypothesis 3: The likelihood of inappropriate prescribing is associated with patient and physician characteristics. To test this hypothesis, the investigators will identify each physician's annual PIP incidence density, calculated by dividing the number of PIP they issued by the total number of prescriptions they provided over the study period and then explore the association of patient and physician level covariates with patient outcomes.

The investigators will test these hypotheses in the framework of a retrospective cohort study which the investigators will conduct using Ontario's large health administrative and population databases. These are housed at the Institute for Clinical Evaluative Sciences (ICES) and contain information on both hospital and outpatient use of health services, as well as demographic and socioeconomic data. Patients included in the study will be all OHIP (Ontario Health Insurance Plan) eligible patients aged 66 yrs of age and older who have been issued at least one prescription between April 1st 2003 and March 31st 2013.

The investigator team, housed at ICES@uOttawa, has extensive experience and expertise with the analysis of these databases, and has the support and resources necessary to successfully carry out this study.

Detailed Description

Objective: The overall objective of the study will be to describe the occurrence of Potentially Inappropriate Prescribing (PIP) in Ontario's elderly (\>65 years) population, assess the health and economic burden associated with it, and evaluate interventions aimed at mitigating its effects.

Hypothesis 1: Instances of Potentially Inappropriate Prescribing are frequent and costly.

To test this hypothesis, the investigators will apply a subset of the STOPP criteria and Beers criteria to Ontario health administrative data to identify instances of potentially inappropriate prescribing, and estimate potential savings, both direct and indirect, which could be achieved by reducing inappropriate prescribing.

Hypothesis 2: ED visits and hospitalizations are significantly associated with Potentially Inappropriate Prescribing

To test this hypothesis, the investigators will estimate the attributable fraction of ER visits and hospitalizations associated with different frequencies of PIP using multivariate methods and survival analysis.

Hypothesis 3: The likelihood of inappropriate prescribing is associated with patient and physician characteristics.

To test this hypothesis, the investigators will identify each physician's annual PIP incidence density, calculated by dividing the number of PIP they issued by the total number of prescriptions they provided over the study period and then explore the association of patient and physician level covariates with patient outcomes.

Background: Adverse drug events are common in the elderly, and contribute significantly to emergency room (ER) visits and unplanned hospitalizations. Patients aged sixty-five and over currently represent over 14% of the Canadian population, yet spending on prescription medications by seniors accounts for over 40% of all retail prescription drug sales. This is equivalent to a per capita spending on prescription drugs by seniors that is three times the Canadian average. A recent Irish study showed that, of 600 elderly patients admitted to hospital for an acute illness, 25% of them had one or more adverse drug events, of which two thirds had contributed to the hospitalizations. Of these adverse events contributing to hospitalizations, 69% were deemed avoidable. A number of tools and strategies have been developed to identify potentially inappropriate prescribing (PIP), however, until recently, none of the commonly used tools had been shown to reliably predict adverse events. The STOPP/START criteria (Screening Tool of Older Persons' potentially inappropriate Prescriptions / Screening Tool to Alert doctors to Right Treatment) was recently compared to the long-standing Beers criteria, and found to detect adverse drug effects that are causal or contribute to hospitalization in elderly patients with acute illness 2.8 times more often than the Beers criteria.

The application of these criteria is usually done in a clinical context, which involves time-intensive and expensive chart reviews. There are relatively few studies looking at appropriateness of prescribing at the population level, using health administrative data. Applying tools to assess appropriateness of prescribing, such as a subset of the STOPP criteria, to health administrative data can provide a unique opportunity to assess both the frequency of potentially inappropriate prescribing and its associated costs, in terms of both medication and health services use at the population level.

Methods: To achieve these aims, the investigators will conduct a retrospective cohort study using Ontario's large health administrative and population databases, that contain information on both hospital and outpatient use of health services, as well as demographic and socioeconomic data.

This study will be conducted using Ontario administrative health databases housed at the Institute for Clinical Evaluative Sciences (ICES), which will be accessed from the ICES@uOttawa site.

Benefits of our work: By using health administrative data from the Institute for Clinical and Evaluative Sciences (ICES) we expect to identify factors, both at the patient and prescriber levels, that are associated with poor prescribing, and to show that a measure already in place in some practice settings is effective at improving not only the quality of prescribing, but also at reducing adverse outcomes associated with poor prescribing. This evidence can provide the basis for targeted policy measures aimed at improving prescribing quality and outcomes for Ontario seniors, and reducing costs.

Recruitment & Eligibility

Status
UNKNOWN
Sex
All
Target Recruitment
2000000
Inclusion Criteria
  1. Individuals eligible for participation in the study will include all patients who were:
  • continuously eligible for OHIP (Ontario Health Insurance Plan) coverage,
  • issued at least one prescription (of any type) during the accrual period (between April 1st, 2003 and March 31st, 2013),
  • 66 years of age or older at the date of first dispensation during the accrual period; this is necessary to ensure the availability of one year of background information on medication and health services use for all patients.
Exclusion Criteria
  1. Patients will be excluded if:
  • They do not have a valid OHIP number. This includes individuals whose health care is provided by other plans (e.g. First Nations people living on reserves, members of the Canadian Armed Forces, and refugee claimants) and is therefore not captured by ICES data.
  • Patients will also be excluded if they were not OHIP-eligible for at least one year prior to the index date, or one year after the index date, or if they do not have continuous OHIP coverage between these two dates; this is necessary to ensure that predictors and outcomes of PIP can be adequately captured.
  • Patients not dispensed any prescription medication will not be included in the study.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Time to any outcomeUp to 90 days after index date

Time between first PIP and first of ER visit, hospitalization or death, occurring within the time window for 'PIP relevant outcomes' (usually up to 3 months after an instance of PIP, but may be longer for some criteria)

Secondary Outcome Measures
NameTimeMethod
Time to hospitalizationUp to 90 days after index date

Time between first PIP and first hospitalization

Time to ER visitUp to 90 days after index date

Time between first PIP and first ER visit

Time to deathUp to 90 days after index date

Time between first PIP and death

© Copyright 2025. All Rights Reserved by MedPath