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Transcript of 1 Health Informatics Centre: Using routine data to support clinical research Prof Peter Donnan, Dr...
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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
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
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
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