Using linked electronic health records to identify patients at high risk of severe liver disease and its complications
Lead Research Organisation:
University College London
Department Name: Structural Molecular Biology
Abstract
Strategic Research Priority: Bioscience for Health
The main objective of this investigation is to guide disease risk stratification of adults in primary care.
Using linked electronic health record data (GP records, hospital admissions, outpatient data, mortality and social deprivation data), the specific aims are to:
-Determine the incidence of and estimate time to severe liver disease outcomes after abnormal liver function tests (LFTs) recorded in primary care.
-Identify factors that predict the occurrence of severe liver disease after abnormal LFTs recorded in primary care.
-Determine whether patients are at increased transient risk of liver disease complications after a common infectious illness.
-Identify factors that affect the odds of severe liver disease in patients with normal LFTs.
-Identify factors that predict the odds of severe liver disease in those without LFT test results.
The research will help identify people at greatest risk of severe liver disease. We anticipate the results of this study may guide patient follow-up, referral to specialist care, vaccination guidelines and enable development of targeted health interventions to prevent or delay the onset of severe liver disease.
The main objective of this investigation is to guide disease risk stratification of adults in primary care.
Using linked electronic health record data (GP records, hospital admissions, outpatient data, mortality and social deprivation data), the specific aims are to:
-Determine the incidence of and estimate time to severe liver disease outcomes after abnormal liver function tests (LFTs) recorded in primary care.
-Identify factors that predict the occurrence of severe liver disease after abnormal LFTs recorded in primary care.
-Determine whether patients are at increased transient risk of liver disease complications after a common infectious illness.
-Identify factors that affect the odds of severe liver disease in patients with normal LFTs.
-Identify factors that predict the odds of severe liver disease in those without LFT test results.
The research will help identify people at greatest risk of severe liver disease. We anticipate the results of this study may guide patient follow-up, referral to specialist care, vaccination guidelines and enable development of targeted health interventions to prevent or delay the onset of severe liver disease.
Organisations
People |
ORCID iD |
| Alastair John O'Brien (Primary Supervisor) | |
| Suvi Harmala (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/M009513/1 | 01/10/2015 | 31/03/2024 | |||
| 1628792 | Studentship | BB/M009513/1 | 01/10/2015 | 17/11/2019 | Suvi Harmala |
| Description | Using electronic health records (info on patient characteristics, lab test results, underlying disease and medications, routinely collected during GP and hospital visits), I developed a risk prediction model that can how high the risk of cirrhosis is for those patients who have had their liver blood tests checked and whose results have been outside what is considered a normal result. I also conducted an initial evaluation of the model to understand how well the model actually works (predicts) and in my future work I am looking to test the accuracy of these predictions further. In addition, as a result of a systematic review of available evidence on the effects of influenza vaccine in patients with liver disease, I found that although influenza vaccine does not seem to protect against death (from any cause), it does protect these patients from hospitalisation. |
| Exploitation Route | The model I developed could help guide patient referrals from the GP to secondary care, identify patients who would benefit from targeted preventative interventions and those patients who should perhaps not be worried about the test results. The results of the influenza vaccine effectiveness review could help doctors explain to liver disease patients who should ideally be vaccinated against flu why it would be beneficial to be vaccinated. |
| Sectors | Healthcare |
| Description | LIDo conference grant fund |
| Amount | £724 (GBP) |
| Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 11/2018 |
| End | 11/2018 |
| Description | Professional Internship for PhD Students -grant |
| Amount | £2,500 (GBP) |
| Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2018 |
| End | 04/2018 |
| Description | UCL HEIF Knowledge Exchange and Innovation Fund |
| Amount | £3,281 (GBP) |
| Organisation | University College London |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 01/2018 |
| End | 04/2018 |