Division of Population Health Sciences

Royal College of Surgeons in IrelandColáiste Ríoga na Máinleá in Éirinn

Connected health: collaborative opportunities for ICON and academia

Tom Fahey

Professor of General Practice, RCSI Medical School & Principal Investigator, HRB Centre for Primary Care Research

Division of Population Health Sciences

Overview

• Background

• Collaborative opportunities– Exploring potential of large databases– Patient safety– Quality of care– Education and training of graduates

Division of Population Health Sciences

Overview

• Background

• Collaborative opportunities– Exploring potential of large databases– Patient safety– Quality of care– Education and training of graduates

Division of Population Health Sciences

My own background

• Professor of General Practice, RCSI 2006 onwards

• Medical graduate UCD, trained epidemiology & Public Health (TCD & Oxford)

• Previously (UK 14 years)– Professor (University Dundee)– SL (University of Bristol)– L (University of Oxford)

Division of Population Health Sciences

Roles

• Professor & Head of Department

• Principal investigator HRB Centre for Primary Care Research

• Chair of Research, Irish College of General Practitioners

• Other roles– Academic collaborator EU FP7 TRANSFoRm– Medical advisory group Irish Medicines Board

Division of Population Health Sciences

Division of Population Health Sciences

Overview

• Background

• Collaborative opportunities– Exploring potential of large databases– Patient safety– Quality of care– Education and training of graduates

Division of Population Health Sciences

GP Electronic Health Record (EHR)

Division of Population Health Sciences

EHR

• UK

• Ireland

Division of Population Health Sciences

Division of Population Health Sciences

Division of Population Health Sciences

Division of Population Health Sciences

Division of Population Health Sciences

Division of Population Health Sciences

Division of Population Health Sciences

Trial data query system

Division of Population Health Sciences

Recruitment RCT

Division of Population Health Sciences

Visualisation- patient recruitment

Division of Population Health Sciences

Diagnostic code recoded- type 1 NIDDM

Division of Population Health Sciences

Overview

• Background

• Collaborative opportunities– Exploring potential of large databases– Patient safety– Quality of care– Education and training of graduates

Division of Population Health Sciences

TRANSFoRm- WP4 patient safety

WP4 Evidence Repository

Clinical Evidence Service

WT 4.5 Evidence Mining and Analysis

Research Study Designer WT 5.2GP EHRs

With CDSS

Evidence Analysis & Extraction Tool

Evidence Management

Tools

Study Criteria Design

Find Eligible Patient

Research Study Management

Recruit Eligible Patient

Study Data Management

Division of Population Health Sciences

Overview

• Background

• Collaborative opportunities– Exploring potential of large databases– Patient safety– Quality of care– Education and training of graduates

Division of Population Health Sciences

Potentially Inappropriate Prescribing (PIP)

• PIP is prevalent in the older population (> 70 years)• Republic of Ireland 36%• Northern Ireland 34%• United Kingdom 29%

Division of Population Health Sciences

The prevalence of the most common STOPP/START PIP indicators across three regions

Division of Population Health Sciences

OPTI-SCRIPT study development

Division of Population Health Sciences

Study overview

PCRS – National Contemporaneous Control

- Observational comparison to national prescribing data (376,858 patients, 2,000+ practices)

Division of Population Health Sciences

OPTI-SCRIPT website

Division of Population Health Sciences

Division of Population Health Sciences

OPTI-SCRIPT RCT results

• Participants • 21 GP practices (32% cluster response rate)• 196 patients (37% response rate)

• Minimisation

Intervention Control11 practices99 patients

10 practices97 patients

Division of Population Health Sciences

Study design & methodology – cluster RCT

• Primary outcome measure: • Proportion of patients with no PIP• Mean PIP per group

• Data collection baseline & immediate post intervention • Between group differences:

• Random effects logistic regression • Cluster mean • Random effects poisson regression

• Process evaluation

Division of Population Health Sciences

Outcome – Proportion with no PIP

Group N Number of patients with no PIP

% of patients with no PIP

Intervention 99 47 47.5

Control 97 22 22.7

Adjusted odds ratio = 3.06 (95% CI 1.4,6.5; P=0.004)*

*adjusted for gender, age, baseline PIP, number repeat medications, GP practice size

Division of Population Health Sciences

National contemporaneous control – PCRS

• Intervention period, Sep 2012 – August 2013 prevalence of 38%

• Odds of having no PIP in OPTI-SCRIPT intervention compared to odds of having no PIP in the national PCRS cohort

Odds Ratio 95% CI

2.49 1.68, 3.69

Division of Population Health Sciences

Overview

• Background

• Collaborative opportunities– Exploring potential of large databases– Patient safety– Quality of care– Education and training of graduates

Division of Population Health Sciences

Overview

• Background

• Collaborative opportunities– Exploring potential of large databases– Patient safety– Quality of care– Education and training of graduates

Division of Population Health Sciences

Division of Population Health Sciences

Discussion

• Collaboration

• Joint funding– HRB Centre renewal– Horizon 20:20

• Training of graduates