The PIP-STOPP Study (PIP-STOPP)

September 21, 2015 updated by: Lise Bjerre, Bruyere Research Institute

Assessing Potentially Inappropriate Prescribing (PIP) and Predicting Patient Outcomes in Ontario's Elderly Population Using the Modified STOPP Criteria in Large Administrative Health Databases (the PIP-STOPP Study)

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.

Study Overview

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.

Study Type

Observational

Enrollment (Anticipated)

2000000

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

66 years and older (Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Patients included in the study will be all OHIP (Ontario Health Insurance Plan) eligible patients, 66 years of age or older and receiving at least one prescription medication during study accrual period.

Description

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 Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Time to any outcome
Time Frame: Up 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)
Up to 90 days after index date

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Time to ER visit
Time Frame: Up to 90 days after index date
Time between first PIP and first ER visit
Up to 90 days after index date
Time to hospitalization
Time Frame: Up to 90 days after index date
Time between first PIP and first hospitalization
Up to 90 days after index date
Time to death
Time Frame: Up to 90 days after index date
Time between first PIP and death
Up to 90 days after index date

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Lise M Bjerre, MD, Clinician Investigator

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start

September 1, 2014

Primary Completion (Anticipated)

March 1, 2017

Study Completion

December 7, 2022

Study Registration Dates

First Submitted

September 18, 2015

First Submitted That Met QC Criteria

September 21, 2015

First Posted (Estimate)

September 22, 2015

Study Record Updates

Last Update Posted (Estimate)

September 22, 2015

Last Update Submitted That Met QC Criteria

September 21, 2015

Last Verified

September 1, 2015

More Information

Terms related to this study

Other Study ID Numbers

  • 287245-HPM-BRUY-46830

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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