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Referral to a new psychological therapy service is associated with reduced utilisation of healthcare and sickness absence by people with common mental health problems: a before and after comparison
  1. Simon de Lusignan1,
  2. Tom Chan1,
  3. Glenys Parry2,
  4. Kim Dent-Brown2,
  5. Tony Kendrick3
  1. 1Department of Health Care Management and Policy, University of Surrey, Guildford, UK
  2. 2Centre for Psychological Services Research, ScHARR, University of Sheffield, Regent Court, Sheffield, UK
  3. 3Hull-York Medical School, University of Hull, Hull, UK
  1. Correspondence to Dr Tom Chan, Population Health Sciences and Education, St George's, University of London, Canmer Terrace, London SW17 0RE, UK; tchan{at}


Background Improving Access to Psychological Therapies (IAPT) is a new programme designed to reduce disease burden to the individual and economic burden to the society of common mental health problems (CMHP). This is the first study to look at the impact of IAPT on health service utilisation and sickness absence using routine data.

Method The authors used pseudonymised secure and privately linked (SAPREL) routinely collected primary, secondary care and clinic computer data from two pilot localities. The authors explored antidepressant prescribing, accident and emergency and outpatients attendances, inpatient stays, bed days, and sick certification. The authors compared the registered population with those with CMHP. The authors then made a 6 months before and after comparison of people referred to IAPT with age–sex and practice-matched controls.

Results People with CMHP used more health resources than those without CMHP: more prescriptions of antidepressants 5.25 (95% CI 5.38 to 5.13), inpatient episodes 4.89 (95% CI 5.0 to 4.79), occupied bed days 1.25 (95% CI 0.95 to 1.55), outpatient 1.5 (95% CI 1.40 to 1.63) and emergency department attendances 0.34 (95% CI 0.31 to 0.37), and medical certificates 0.29 (95% CI 0.26 to 0.32). Comparison of service utilisation 6 months before and after referral to IAPT was associated with reduced use of emergency department attendances (mean difference: 0.12 (95% CI 0.06 to 0.19, p<0.001)). However, the number of prescriptions of antidepressants increased mean difference −0.15 (95% CI 0.02−0.29, p=0.028).

Conclusions People with CMHP use more healthcare resources. Referral to the IAPT programme is associated with a subsequent reduction in emergency department attendances, sickness certification and improved adherence to drug treatment.

  • Behavioural disciplines and activities
  • medical record systems
  • computerised
  • healthcare disparities
  • healthcare quality
  • family practice
  • access and evaluation
  • mental disorders
  • depressive disorders
  • anxiety disorders
  • community care
  • health policy
  • health service use
  • mental health inequalities
  • prim/sec interface

Statistics from


In the UK, the national guidelines body, the National Institute for Health and Clinical Excellence, recommends the use of psychological therapies, including cognitive behavioural therapy,1 2 in the treatment of depression and anxiety. It costs less to provide these treatments than to fund benefit payments to people with mental health problems who are unable to work.1 3 However, such therapies have been hitherto largely unavailable in primary care.4 The Improving Access to Psychological Therapies (IAPT) programme, a government initiative, aims to reduce economic burden to the society of psychological illness and enables people to cope better with their mental health problems through timely access to effective interventions.5

Evaluation of the effects of an intervention on a local healthcare system is challenging. Evaluation of IAPT intervention using clinic or primary care data separately has not provided data about the system impact of a programme, particularly on hospital utilisation. These health utilisation data are outcomes that are important in addition to the psychological outcomes of therapy and patient satisfaction. This paper does not report psychological outcomes of the individuals referred to IAPT, which are addressed in a report to the Department of Health. We carried out this study using a novel method of anonymous linkage of routinely collected primary, secondary and IAPT clinic data to evaluate whether the new IAPT service altered health service utilisation.


We linked a data set extracted from general practice electronic patient record (EPR) systems to hospital and IAPT data for these patients using a process of fuzzy logic called SAPREL (Secure and Private Record Linkage).6 This process is compatible with the Caldicott principles7 and with emerging data processing standards in clinical informatics.8 These linked data enable the tracking of health service utilisation of individual patients of the study population across primary, secondary and tertiary healthcare services. The data set included patients often practices at each of two demonstration sites: one in a northern city and one in east London with a total list population of 152 328 patients. The General Practice (GP) electronic patient record (EPR) data are comprehensive data recorded by the GP or other clinical professional at the point of care.9 10 The hospital data are ‘Secondary Uses Service’ data; these are hospital episode statistics11; generally coded by medical record data entry staff after the episode is completed based on their interpretation of written clinicians' notes. Finally, we extracted IAPT data; the IAPT clinics record a nationally specified data set; though the NHS unique identifier, NHS number12 is often not recorded (figure 1).

Figure 1

Unique identifiers (UID) used to link the three databases.

Data were collected from GP practices in December 2009 using MIQUEST (Morbidity Information QUery and Export SynTax), a Department of Health-approved data interrogation software. We only extracted coded data (coded using the Read code system)13 but not narrative or ‘free-text’ record; we processed these data using well-tested processes.14 15 The data set extracted included person identifiers (name, date of birth, full postcode), mental health problems, prescriptions of psychotropic medications and records of medical certificates. Strong identifiers such as name and date of birth were transiently processed and de-identified within the GP practice by creating a unique pseudonym for each patient. Postcodes were transformed into deprivation scores using the Multiple Deprivation Index (MDI) within GP computer systems. All interim files were permanently deleted prior to leaving the GP practices. We grouped those who have diagnosis of a neurotic or affective disorder into a variable that we labelled common mental health problems (CMHP). We also restricted our analysis to those with a CMHP on or after 1st April 2007, that is, the last 18 months of the study period.

Hospital episode data for the patients registered with the participating practices between 1 October 2007 and 30 April 2009 were extracted on our behalf by the information services of the local NHS. The only strong personal identifier, NHS number, was extracted and de-identified (pseudonymised) within the Primary Care Trust premises. We extracted activity data about: accident and emergency (A&E) and outpatient attendances and hospital admission including primary diagnosis and length of stay.

We collected records from the IAPT services between 01 October 2007 and 30 September 2008 for patients of the participating GP practice. IAPT service activity data extracted included date of referral, date of assessments, number and date of therapeutic sessions in the ‘Stepped Model of Care’, and the global health and social well-being outcome measures.

Analysis of the outcomes of IAPT intervention was based on ‘intention to treat’, that is, all those referred to IAPT whether or not they engaged with the service or completed their course of therapy.16 17 A power calculation was performed to ensure that the study size is viable in detecting differences in the outcome measures. We used a range of descriptive and inferential statistical procedures to compare differences in the samples and outcomes.

We compared utilisation of health services 6 months before and after for people referred to IAPT against a control group, controlled for age, sex and GP practice with a ratio of cases to control, 1:6. The date used to define the ‘cut-off’ between ‘before’ and ‘after’ was the date of the first therapeutic session; if that date was missing, we used the date of the initial assessment. For those who declined assessment or therapy and for the control group, the cut-off date used is the median number of days between referral and first therapeutic session: 44 days. Finally, we report differences between the two localities and practices.

The study was approved by the National Research Ethics Service (No: 08/H0715/101) and by the Patient Information Advisory Group (PIAG) for section 60 exemption (now the National Information Governance Board and Section 158 exemption)18 as we transiently hold patient identifiable data (PIAG 6-06(h)/2008). SAPREL was commended by PIAG as an example of best practice.19


Practice population and people referred to IAPT

The mean ages of the adult patients of the list practice population are about 2 years older than those referred to IAPT (table 1). The mean age conceals the fact that the majority of people referred to IAPT are in the age bands between 20 and 54, with very few people aged 65 years and older (figure 2). While the number of adult female and male patients are broadly equally distributed in the GP list population (female: 49.7%; male: 50.3%), there are clear gender differences between the GP list population and the IAPT populations. Nearly two-thirds of the clients of the IAPT services are women (χ2 p<0.001).

Table 1

Characteristics of GP list population compared with those referred to IAPT

Figure 2

Comparing adults referred to IAPT compared with those who have not.

‘White’ ethnicity was over-represented in the IAPT population at 47.9% compared with 33.2% in the practices' adult population (χ2 p<0.001). The majority of those referred to IAPT were from the bottom two MDI deciles: 30.5% in the 9th decile and 32.0% in the 10th decile. There are no statistically significant differences in the level of deprivation between those referred and those not referred to IAPT.

People with CMHP

Just under a quarter (22%) of adults had a recorded CMHP in the GP EPR system. Around 10% of the adult population had a recorded CMHP and 7.1% a recorded diagnosis of affective disorders in the 18 months between 1 April 2007 and 31 December 2009.

While most of the people referred to IAPT (69.2% 774/1118) had a CMHP, this is a small proportion (6.3%) of the total with CMHP (χ2 p<0.001). The effect of IAPT on health service utilisation at the population level was likely to be ‘diluted’ by the relatively small number of people referred to IAPT for intervention.

Healthcare utilisation

We used antidepressant prescriptions and issues of Medical certificates, or sick notes, as surrogates of primary healthcare utilisation. The utilisation of health services of adults with a recorded CMHP is greater than those without a recorded CMHP for all the indicators of health consumption in this study. Those with a CMHP received an average of 5.25 (95% CI 5.38 to 5.13) for more prescriptions for antidepressant and 4.89 (95% CI 5.0 to 4.79) for more sick notes over the 18-month period (table 2). People with a recorded CMHP received nearly 10 times more sick notes than other adult patients. Those with a recorded CMHP also used more hospital services than other adult patients. The mean differences between those with CMHP were all in the direction of patients requiring more care, with more inpatient episodes 0.29 (95% CI 0.26 to 0.32), more occupied bed days 1.25 (95% CI 0.95 to 1.55), more outpatient appointments 1.5 (95% CI 1.40 to 1.63) and more A&E attendances 0.34 (95% CI 0.31 to 0.37).

Table 2

Health services utilisation of people with and without CMHP

Before and after study of the effect of referral to IAPT

The intervention group used fewer healthcare resources measured in terms of number of medical certificates issued, number of admissions, number of hospital bed days and number of A&E attendances. These are represented by a positive value of the mean changes before and after IAPT (table 3). However, the intervention group received more prescriptions of antidepressants and had more outpatient appointments after the intervention than before. Comparison of the changes between the intervention and the control groups showed that IAPT referral was associated with a greater reduction in all health utilisation indicators for the intervention group apart from prescription of antidepressants. The findings are statistically significant for prescription of antidepressants (−0.15, 95% CI −0.29 to −0.02, p=0.028), number of sick notes (0.11, 95% CI 0.04 to 0.17, p=0.002) and number of A&E attendances (0.12, 95% CI 0.06 to 0.19, p<0.001).

Table 3

Difference in health consumption in the 6 months before and after IAPT intervention—comparing case and control (adjusted for age, gender and practice)

This analysis was repeated for those with and without a recorded diagnosis of CMHP for the intervention and the control groups (tables not shown). The findings were broadly similar for those with a recorded diagnosis of CMHP, that is, that IAPT intervention was associated with greater reduction in all health utilisation indicators than in the control group apart from prescription of antidepressants; but the difference is only statistically significant for the number of sick notes (0.18, 95% CI 0.08 to 0.29, p<0.001) probably due to smaller numbers involved. For those without a recorded diagnosis of CMHP, IAPT intervention was associated with greater reduction in number of occupied bed days, number of outpatient appointments and number of A&E attendance than in the control group; the difference is statistically significant for the number of A&E attendance only (0.12, 95% CI 0.02 to 0.22, p=0.021).

Variation between localities and practices

The level of recording of ethnicity codes differed significantly between the two demonstration sites. The London site with a higher ethnic mix has a much greater proportion of the GP list population with a recorded ethnicity code (at 81.4%) compared with the Yorkshire site (at 35.1%). There was also a different rate of IAPT referral between the GP practices in the locations, though not statistically significant (Mann–Whitney U two-tailed significance p=0.226).

Variations in the outcomes of IAPT intervention between GP practices and study sites were explored. There were no outliers in terms of use of health resources at the level of GP practice. There were significant intersite differences in all the outcome variables, with the northern city study site using more health resources in all the outcome indicators in this study than the Newham study site (table 4).

Table 4

Variation in outcome variables between the northern city and east London localities


Principal findings

The routinely recorded general practice service data suggest that around 20% of people have had a CMHP at some time and around 10% in the last 18 months. People with a recent CMHP used more health resources as indicated by the number of prescriptions of antidepressants and sick notes in primary care and the use of inpatient, outpatient and A&E services in secondary care. Over the 18-month study period, people with a CMHP received nearly 10 times more sick notes than those without a CMHP.

The majority of people referred to IAPT were from the lowest two deciles of the MDI, broadly reflecting the levels of deprivation in the pilot sites. Relatively few people aged 65 years and older were referred to IAPT services, and there were differences among ethnic and gender groups, with more people of white ethnicity and women being referred.

Compared with the control group, people referred to IAPT services used fewer healthcare resources 6 months after therapy in terms of number of sick notes and number of A&E attendances. Within this group, there was little difference between those who did or did not have a recorded GP diagnosis of a CMHP. The increase in antidepressant use may signify better compliance with therapy or possibly indicate that those referred to IAPT were presenting in a more acute phase. There was a reduction in the number of inpatient care episodes and number of occupied bed days, though these differences were not significant.

Implications of the findings

People with CMHP seem to use greater than average healthcare resources in primary care and have increased sickness absence and hospitalisation; investment in IAPT services was designed to treat their illness more effectively and therefore reduce health service utilisation compared with current practice. These results provide some support for the success of this approach, in that there was a reduction in the use of emergency services for people referred to IAPT.

Referral to IAPT is thought appropriate for people from the whole spectrum of levels of deprivation. The reasons for over-representation of some groups need further exploration. Accessibility of services for people in work, or for whom English is not their first language, may be barriers.

Comparison with the literature

Recognition of the psychological element of disease is therapeutic, and this approach underpins the IAPT approach to patients' problems in primary care.20 21 To date, reviews have focused on evaluation of the service22 23 or on comparing psychological therapy with usual practice,24 rather than its impact at the population level. There are no published studies that link clinical data in primary and secondary healthcare services to evaluate the system impact of the IAPT programme. The findings of this study would support a decision to increase expenditure on the IAPT programme, despite cuts or no growth elsewhere in the health system.

Limitations of the method

We potentially had too short a period of data collection, and we were unable to access routine data on secondary mental health service usage at the time of the study. In this record-based research, we are unable to control for confounding factors when comparing groups of people within the practices, but the comparison of importance is within the referral group, before and after IAPT.

There are limitations in working with routinely collected data25: it is inevitably incomplete. Primary care data now have a very accurate denominator since the creation of a nationally unique identifier for patients. Repeat prescribing and acute prescribing are generally complete and accurate as this is the one activity which saves GPs time; lab links have meant that pathology data are largely complete and accurate. Pay-for-performance has greatly improved coding of data for conditions included in the list of indictors. However, the burden of needing to ask patients to complete depression questionnaires when some codes are used has created perverse incentives and some practitioners may avoid these.26 Finally, coding is not a neutral process, some patients may present with physical symptoms and clinicians may feel that it is not appropriate to give this a psychological diagnosis.27

The IAPT clinics use one of two recommended brands of software approved by the Department of Health. We found that other than NHS number, other fields in these systems appeared to be fully completed. Hospitals are very good at recording activity data, partially driven by the need to ensure that payment is received for caring for patients with complex needs particularly since the ‘payment-by-results’ scheme in 2003/4.28

Call for further research

A larger linked data study including populations drawn from a wider range of social groups may provide more generalisable data about the effectiveness of IAPT. Longitudinal data might provide insight into the relationship between depression and long-term conditions.


This study is the first linked data study of its type—bringing together primary care, hospital and clinic data. The study has the limitations associated with any study of routine data, yet even so there were marked differences between those with CMHPs and people referred to IAPT and the rest of registered population. At a time where there is pressure to control increasing health costs, this study suggests that IAPT may contribute to reducing health service usage.

What is already known on this subject

One of the six adults in the UK suffers from a common mental health problem, generally depression or anxiety disorder. Common mental health problem are associated with increased utilisation of healthcare resources and sickness absence across a range of conditions. Effective psychological therapies exist for common mental health problem particularly cognitive–behavioural therapy. However, they are generally unavailable within primary care, and their effectiveness has not been studied at the locality level.

What this study adds

The UK Department of Health set up a programme to improve access to psychological therapies, and this study is the evaluation of its pilot sites. This evaluation study used a unique method of private data linkage method to join general practice, hospital and psychological clinic data. We found that people with CMHP consume more healthcare resource. Compared with controls, referral to IAPT is associated with reduced number of sick notes and use of accident and emergency and possibly better adherence to therapy.


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  • Funding Practices and patients for the use of their pseudonymised data. This study was funded by the National Institute for Health Research, Service Delivery and Organisation Programme (NIHR SDO) programme as part of a wider evaluation of Improving Access to Psychological Therapies (IAPT) demonstration sites. The pseudonymisation and data linkage, SAPREL (Secure and Private Record Linkage) was carried out by Sapior Ltd and funded by the DH IAPT programme and was described in a separate protocol and ethics application.

  • Competing interests None.

  • Ethics approval This study was conducted with the approval of The National Research Ethics Service (No. 08/H0715/101) and by the former Patient Information Advisory Group.

  • Provenance and peer review Not commissioned; not externally peer reviewed.

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