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Health Informatics Centre: Using routine data to support clinical

research

Prof Peter Donnan, Dr Colin McCowanPopulation Health Sciences

University of Dundee

• Holds patient specific datasets for entire population of Tayside (since early 90’s) & Fife (last few years)– Encashed prescribing– Hospital admissions– Demographic dataset– Cancer registry

• Datasets are linked, anonymised and made available for approved research projects

HIC DatasetsDispensed prescriptions 1993-date (variable completeness)

Dental datasets – local, national

Walker dataset: across 3 generations, linked via Ninewells obstetric records – 1/3 with CHI

Lab data (bacteriology, haematology, biochemistry, etc) 1992 on

Specialty data on patients with diabetes, cardiovascular, COPD, thyroid & liver disease; maternity, neonatal, geriatric, child health, mental health, cancer…

SMR datasets from Information Statistics Division of NHS Scotland

General Registrar Office data: date & cause of death

Scottish Index of Multiple Deprivation

5/28

Community Health Index Number

Date of Birth Gender Check digit

07 10 64 02 5 0

6/28

Drug data-CHI

Lab data-CHI

Drug data-CHI

Lab data-CHI

Data linkage and anonymisation

Enter data, find CHI

Drug data, lab data

Fully anonymised but linked data

CHI labelled dataFully identifiable data

Paper prescription

Lab result -ID

Drug data, lab data

Drug data, lab data

Paper prescription -ID

Paper prescription-ID

Lab result -IDLab result-ID

Drug data-CHI

Lab data-CHI

Drug data, lab data-CHI

Analysis

Find CHI

Link using CHI

AcademiaHICNHS

Drug data, lab data-CHI

Drug data, lab data-CHI

DeleteCHI

7/28

Information governance and HICPhysical security: • Isolation of servers holding identifiable data, of those working with it; • Reliable backup and recovery mechanisms• Separation of functions on NHSNet, JANET

Privacy model:• Inherited from NHS Scotland’s Information Systems Division• Evaluated by EU Data Protection expert Petra Wilson: “the proper legal framework

for the use of anonymisation techniques as demonstrated by MEMO” (BMJ 2004)

Governed by Confidentiality & Privacy Advisory Committee • Same pt. representative chair as ISD Privacy Advisory Committee• Members include lawyer, GP, Caldecott Guardian

Management tools:• Standard Operating Procedure• Problem reporting mechanism on intranet• Project management system enforces SOP• Annual external audit by information security experts + table of issues reviewed

monthly by HIC Exec

Benefits of HIC Data• Population based

– No socio-economic bias– Socio-economic status– Mostly single centre treatment

• Outcomes data– GRO : all cause & disease specific mortality

• Hospital Discharge, Cancer Registry etc• Specialist data sets: research & clinical• Prescribing, lab results

Prescribing to older people

Aims & Research Questions

To investigate if there are differences in potentially inappropriate medications between older people living in their own home compared with people living in nursing or residential homes

1. To determine if there are differences in prescribing and meeting Beers criteria guidelines between patients by place of residence for all classes and by individual criterion

2. To assess whether receiving a PIM was associated with an increased risk of death

3. To examine any differences in PIM prescribing by practice

Beers Criteria for potentially inappropriate medication in the elderly

• Limited clinical trial evidence of use of drugs in the elderly.• Current guides to assess potentially inappropriate prescribing based

on expert consensus e.g. Beers Criteria.• The Beers criteria are one of the most widely used consensus criteria

for medication use in older adults (last updated 2003), although there is increasing concern about their appropriateness

Drug Concern Severity Rating (High or Low)

Amitryptyline Because of its strong anticholinergic and sedation properties, amitryptyline is rarely the antidepressant of choice for elderly patients.

High

Non-Cox-Selective NSAIDS:Naproxen, Piroxicam

Have the potential to produce GI bleeding, renal failure, high blood pressure and heart failure.

High

Methods – Identifying the population• Care home addresses obtained from the relevant local

authorities & other sources• Compared to electronic register of addresses held by NHS

Tayside on all patients • 377 addresses were manually checked where there was still

uncertainty if they aplied to a care home• Patient’s classed as living at home if address did not match

any of those on the addresses of the care home list • Patients classed as in care if their address matched one from

the care home list

MethodsPrescriptions

Prescriptions were obtained for all patients dispensed in 2005 and 2006. Information available included, Patient Chi Number, Drug Name, Prescription Date, Formulation Code, Strength, Quantity, Directions, BNF Code and prescribing practice.

BNF categories (Drug Class)BNF codes were grouped according to class of drugs e.g.4.2.1 - Antipsychotic drugs, or5.1.1.3 - Broad-spectrum penicillins

Descriptive statistics of patients aged 65 -99 years, 2005-2006

At Home In CareNumber of Patients (%) 65,742 (93.5) 4,557 (6.5)

Mean Age (std dev) 75.2 (6.8) 84.5 (7.5)Age Categories n (%)

66-70 20,034 (30) 239 (5)71-80 31,148 (47) 1,065 (23)81-90 12,934 (20) 2,176 (48)91-99 1,626 (2) 1,077 (24)

Female sex n (%) 37,497 (57.0) 3,296 (72.3)No. of deaths (%) 5,321 (8.1) 1,790 (39.3)

Mean no. of prescriptions (95% CI)

66.7 (66.28-67.22) 113 (110.37-115.56)

Mean no. of drug classes (95% CI)

8.8 (8.73-8.82) 11.6 (11.39-11.77)

Relationship between receiving a PIM with variables of interest

Explanatory variable Odds Ratio (95% CI)Unadjusted Adjusted*

Age Categories n (%)66-70 1.0 1.071-80 1.16 (1.12-1.21) 0.91 (0.88-0.95)

81-90 1.18 (1.13-1.24) 0.76 (0.72-0.80)

91-99 0.98 (0.89-1.07) 0.65 (0.58-0.72)

Male 1.0 1.0Female 1.37 (1.33-1.42) 1.22 (1.17-1.26)

Polypharmacy(No. of drug classes)

1.19 (1.18-1.19) 1.19 (1.19-1.19)

At home 1.0 1.0In care 1.32 (1.24-1.40 ) 0.94 (0.87-1.01)

Criteria At Home %

In Care %

Odds Ratio (95% CI) Severity RatingUnadjusted Adjusted*

Long Acting Benzodiazepines

6.36 11.13 1.85 (1.68-2.04) 1.62 (1.45-1.81)† High

Nitrofurantoin 2.46 5.84 2.46 (2.15-2.81) 1.52 (1.30-1.76)† High

Fluoxetine 2.10 4.83 2.37 (2.05-2.74) 2.25 (1.91-2.65)† High

Muscle Relaxants 1.69 3.84 2.32 (1.97-2.73) 1.42 (1.19-1.70)† High

Amitryptyline 7.76 5.99 0.76 (0.67-0.86) 0.59 (0.51-0.67)‡‡ High

NSAIDs 3.92 1.56 0.39 (0.31-0.49) 0.42 (0.33-0.54)‡‡ High

Gastrointestinal antispasmodic

1.06 0.92 0.87 (0.63-1.18) 0.70 (0.51-0.98) ‡‡ High

Practice level prescribing of Beers Criteria drugs

Potentially Inappropriate Medications

• Exceptions will exist within the datasete.g. - Patients may be on a short course of long

acting benzodiazepines.- Patients may be on low doses of

amitrptyline.-A patient may be on NSAIDS while awaiting a

hip replacement.

Key Findings• Older patients in care have higher numbers of prescriptions

and drugs from more classes than those living at home• Around 1/3 of Tayside’s older population have potentially

inappropriate medications according to Beers Criteria• After allowing for age, sex and number of drug classes there

were no differences in overall potentially inappropriate medications between patients in care and those at home

• Polypharmacy is a consistent risk factor associated with potentially inappropriate medications

• The Beers Criteria as a screening tool may not be appropriate although some individual criteria show differences which may be important and need more investigation

Barnett et al. BMJ Qual Saf 2011;20:275-281 doi:10.1136/bmjqs.2009.039818

Psychoactive drug use in older people• Antipsychotics used for

Behavioural and Psychological Symptoms of Dementia– Not very effective– Increasing evidence they are harmful– Little evidence about how commonly used

• Also interested in use of hypnotics, anxiolytics, anti-depressants and long-acting benzodiazepines

Aim• The aim of this study was to examine

prescribing for psychoactive medications for patients living in care homes compared to patients living at home

Methods• Residents of care homes identified as before with recorded date

of entry noted• Extracted all dispensed prescriptions for psychoactive drugs

2005-2006. Examined prescribing for 1 Jan – 25 Mar 2005– Hypnotics (BNF 4.1.1)– Anxiolytics (BNF 4.1.2)– Oral anti-psychotics (BNF 4.2.1)– Tricyclic and related antidepressants (BNF 4.3.1)– SSRI antidepressants (BNF 4.3.3)– Other antidepressants (BNF 4.3.4)

• Examined prescribing for patients admitted to care homes across the study period

Patient Demographics

• Of those in care, 49% in nursing homes, 39% residential homes, 12% mixed type

• Based on patients alive on 25 March 2005

At Home In Care

No. of Patients 66,494 (95.9) 2,813 (4.1)

Mean Age 75.3 years 84.5 years

Female 57.4% 72.9%

Prescribing in 12 week period

Living at home Living in care

Mean no. of items dispensed

7.19 (7.12-7.25) 15.66 (15.11-16.20)

Mean no. of drug classes received

4.02 (3.99-4.04) 5.65 (5.49-5.80)

Psychoactive prescribing in past 12 weeksOdds ratios (95% CI)

adjusted for age & sex

OR 3.65 (3.22-4.15)

OR 1.44 (1.24-2.68)

OR 12.96 (11.26-14.91)

OR 2.26 (1.91-2.68)

OR 1.52 (1.34-1.71)

Any psychoactive medication : At home 15.5%, In Care 41.7%, OR 3.09 (2.84-3.35)

When are drugs started?• 1,715 (2.4%) patients were admitted to a

nursing home in 2005-2006No of patients (%) Started at home

Hypnotics 473 (28) 72%

Anxiolytics 343 (20) 70%

Oral anti-psychotics 500 (29) 72%

Tricyclics 223 (13) 75%

SSRI 431 (25) 73%

Oral anti-psychotics

• 500 patients with an admission 2005-2006 were prescribed an oral antipsychotic– 28% initiated +/- 30 days of admission– Half initiated in 30 days prior to admission– Half initiated in first 30 days after admission

• Median duration of use 280 days (IQR 30-613)– 299 (60%) taking oral anti-psychotics for 6 months

or longer

No of patients

Duration >= 180 days

Continuous OR for stopping

(%) (%) (%) OR (95%CI)

>30 days prior to admission 282 (56) 215 (76) 62 (22) 1.0

Within 30 days prior to admission

70 (14) 29 (41) 27 (39) 0.50 (0.28-0.88)

Within 30 days after admission

71 (14) 30 (42) 25 (35) 0.53 (0.30-0.94)

> 30 days after admission 77 (15) 25 (32) 24 (31) 0.73 (0.41-1.30)

Oral anti-psychotics

Conclusions• Patients in care are more likely to be prescribed

psychoactive drugs• Contrary to expectation, usually initiated before

admission• High rates of anti-psychotic use, and once

started prescribing is usually prolonged• Further work should investigate why drug

initiation occurs, duration of use, and whether prescribing is appropriately reviewed

Conclusions

• There is increased use of potentially harmful drugs for patients in care compared to the community

• Further work should investigate why drug initiation occurs, if it is based on new diagnosis and whether it is short or long term use

Acknowledgements

• Prof Bruce Guthrie, Prof Tom Fahey, Dr Stella Clark, Dougie McPhail, Dr Karen Barnett, Prof Peter Davey, Prof Frank Sullivan, Marie Pitkethley, Dr Claire Stubbings, Dr Parker Magin

• Alison Bell, Chris Hall & Duncan Heather at the Health Informatics Centre for supplying and managing the routine data