Diagnóstico Antecedentes

2.5.1. Background

In the UK, primary care is the first point of contact for medical care (unless in an emergency situation). The general practitioner (GP) can conduct or order tests, prescribe drugs and provide some diagnoses, although many diagnoses may require confirmation from specialists. They also act as the gatekeeper to further specialist care – for example – if an individual presents with symptoms of epilepsy (e.g. recent seizures), the GP may refer the individual for further tests to be performed in a hospital setting (such as an EEG and MRI scan) and refer them

73 to a neurologist for specialised consultation. Generally, a specialist can only be seen through a referral from primary care (the exception being through emergency care) and therefore primary care data should at least capture the initial consultation from which a referral was made.

The Health Improvement Network (THIN) is one of the UK’s largest primary care databases. In 2014, the database contained information on over 12 million patients attending 587 practices (http://csdmruk.cegedim.com/). Data in THIN is collected through an interface (provided by Vision software) which is used by the GP practice to input medical information. When the data is collected out of the system every quarter, it is anonymised to protect patient confidentiality. The data are extracted, cleaned and then structured into tables ready for researchers to analyse. Updates on THIN data are available twice a year.

Researchers receive THIN data in four main data blocks – patient, therapy, medical and additional health data (Figure 1) which collate information recorded during a patient’s visit to their GP as well as information received from other parts of the health system e.g. hospital discharge letters. This includes medical diagnoses and symptoms (based on the hierarchical Read code system),96;97

additional health data on health measures, test results and immunisations, prescriptions, referrals to secondary care and free text information. It also includes demographic information such as the patient’s year of birth and sex, and a marker of social deprivation, the Townsend score. The Townsend score is a postcode based index of deprivation which uses information from the 2001 Census. The score is based on the percentage of unemployment, overcrowded households, no car/van ownership and non-home owners.98;99 _{The THIN data}

files are linked by an anonymous patient identifier. The database also includes a family identifier as well as dates on registration, death and transfer to another practice.

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Figure 1 THIN data structure (Redrawn from Source: CSD-EPIC Research Format THIN data (Version 2.0), 2010)

Data quality indicators have been created which help researchers determine when practices were providing good quality data. The Acceptable Mortality Rate (AMR) date was developed by Maguire et al in 2009 after it was observed in that data that some GP practices had low mortality rates indicating that mortality was not being adequately recorded.100 _{The AMR date measures the year in which the}

death rate in the practice was deemed acceptable in comparison with age/sex adjusted national rates. For research purposes, the use of data only from this date onwards removes under-reporting of deaths and other biases associated with record updating.100 _{A further measure was derived by Horsfall et al - the}

Acceptable Computer Usage (ACU) date which defines when the practice on average was entering at least two therapy records, one medical record and one additional health data record per patient per year.101 _{Both dates can be used to}

define a point in time from which good quality data is likely to have been recorded in a practice.

Research studies using THIN data cover a broad range of conditions, drugs and epidemiology. Studies have included estimation of incidence rates such as for

75 pancreatic and biliary tract cancer, description of prescribing patterns such as mood stabiliser treatment in people with bipolar disorder, and studies of association such as serum bilirubin and the risk of respiratory disease and death.34;102-105 _{Other uses of THIN data have been in health care planning,}

assessment of current clinical practices, and for methodological research.106;107

Outlined below are the general strengths of THIN data for research, and in balance to this, some of its limitations, which have to be borne in mind and addressed in any research study. As THIN is the data source chosen for use in this PhD, the further details of advantages and disadvantages specific to studying medication safety in pregnancy are covered in the next chapter which presents how THIN can be used to identify a mother-child cohort.

2.5.2. Strengths of THIN data for research

 Designed for research

One of the major differences between THIN and insurance claims databases is that THIN is intended for use in clinical research, secondary to clinical management. Thus the data captured is designed to benefit and inform primary care research. Furthermore, the providers of THIN data are continually improving their data and consulting both GP practice users and researchers on how the system and the data can be improved to meet their needs.

 Large sample size

As mentioned, the database holds information for 12 million patients across the UK providing access to potentially large sample sizes for study.

 Representative of general population

All data are anonymised, and are broadly representative of the UK population in terms of sex, age, size of practice and geographic distribution.108

76 Studies of routinely collected data are retrospective however, more importantly, they use prospectively recorded data. This reduces the potential for recall bias whereby the level of exposure information recalled differs depending on whether or not an outcome occurred.

 Real world clinical data

The data is a reflection of clinical practice in the real world amongst a population of individuals who differ in all manners of their health and socio- demographic factors. It reflects real GP behaviours which are also likely to differ but are a true representation of medical care in real time - a stark contrast to the regimented medical care recovered in clinical trials where participants are tended to at specific time points.

2.5.3. Weaknesses of THIN data for research

 Uncollected or poorly recorded information

The main disadvantage in using a database of retrospectively collected routine data is that the data is not collected for a specific research study. Thus, there may be factors which are of interest to a study which are not collected, or are poorly measured. For example, there is limited information on severity the underlying conditions associated with prescribing of antiepileptic drugs.

 Lack of information outside of primary care

Despite the breadth of clinical information collected in THIN, any events such as prescriptions, diagnoses, inpatient stays, which happen outside of primary care may not be well-recorded although discharge letters are sent from hospitals to GPs. This depends on efficient communication of such information to primary care and further accurate input of relevant clinical details into the computer system.

Electronic medical records databases are a powerful source of real world clinical data due to the large number of patients and wide breadth of clinical information contained in such databases. THIN is an excellent example, and furthermore

77 shows how routinely collected electronic medical records can serve both as a clinical management system and for use in research.

2.6. Summary

Designing a study to examine the teratogenicity of drug is challenging. Randomised controlled trials are not a favourable design for concerns over the involvement of pregnant women and the study sample required to study rare outcomes, meaning that research must depend on observational studies. Despite having to address issues around bias, confounding, and access to relevant information, observational data has the capability to provide large samples of women taking drugs in pregnancy, as well a wide range of other health and clinical information. Every observational study has to consider the aforementioned issues and additionally other issues specific to the research question in mind. In this PhD, I will conduct a retrospective cohort study of pregnant women using data from The Health Improvement Network primary care database. Some of the reasons for this choice have been alluded to in the above section on the general merits of THIN. The next chapter expands on why THIN was chosen specifically for this study of pregnant women.

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Chapter 3

Using The Health Improvement Network to Identify a Mother –

Child cohort