How far back do we need to look to capture diagnoses in electronic health records? A retrospective observational study of hospital electronic health record data

How far back do we need to look to capture diagnoses in electronic health records? A retrospective observational study of hospital electronic health record data. Lewis, J., Evison, F., Doal, R., Field, J., Gallier, S., Harris, S., le Roux, P., Osman, M., Plummer, C., Sapey, E., Singer, M., Sayer, A. A, & Witham, M. D BMJ Open, British Medical Journal Publishing Group, 2024.

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Objectives Analysis of routinely collected electronic health data is a key tool for long-term condition research and practice for hospitalised patients. This requires accurate and complete ascertainment of a broad range of diagnoses, something not always recorded on an admission document at a single point in time. This study aimed to ascertain how far back in time electronic hospital records need to be interrogated to capture long-term condition diagnoses.Design Retrospective observational study of routinely collected hospital electronic health record data.Setting Queen Elizabeth Hospital Birmingham (UK)-linked data held by the PIONEER acute care data hub.Participants Patients whose first recorded admission for chronic obstructive pulmonary disease (COPD) exacerbation (n=560) or acute stroke (n=2142) was between January and December 2018 and who had a minimum of 10 years of data prior to the index date.Outcome measures We identified the most common International Classification of Diseases version 10-coded diagnoses received by patients with COPD and acute stroke separately. For each diagnosis, we derived the number of patients with the diagnosis recorded at least once over the full 10-year lookback period, and then compared this with shorter lookback periods from 1 year to 9 years prior to the index admission.Results Seven of the top 10 most common diagnoses in the COPD dataset reached >90% completeness by 6 years of lookback. Atrial fibrillation and diabetes were >90% coded with 2–3 years of lookback, but hypertension and asthma completeness continued to rise all the way out to 10 years of lookback. For stroke, 4 of the top 10 reached 90% completeness by 5 years of lookback; angina pectoris was >90% coded at 7 years and previous transient ischaemic attack completeness continued to rise out to 10 years of lookback.Conclusion A 7-year lookback captures most, but not all, common diagnoses. Lookback duration should be tailored to the conditions being studied.Data may be obtained from a third party and are not publicly available. The data that support the findings of this study are not openly available due to reasons of sensitivity. Data may be accessed on request to the HDR-UK PIONEER acute data hub on provision of permission from the PIONEER Data Trust Committee and provision of a data access agreement. Data are located in controlled access data storage at the PIONEER acute data hub.

@article {Lewise080678,
	author = {Jadene Lewis and Felicity Evison and Rominique Doal and Joanne Field and Suzy Gallier and Steve Harris and Peta le Roux and Mohammed Osman and Chris Plummer and Elizabeth Sapey and Mervyn Singer and Avan A Sayer and Miles D Witham},
	editor = {, and , and Sayer, Avan A and Bartle, Victoria and Cooper, Rachel and Cordell, Heather J and Holding, Ray and Marshall, Tom and Matthews, Fiona E and Missier, Paolo and Pearson, Ewan and Plummer, Chris and Robinson, Sian and Sapey, Elizabeth and Singer, Mervyn and Scharf, Thomas and Wason, James and Witham, Miles D},
	title = {How far back do we need to look to capture diagnoses in electronic health records? A retrospective observational study of hospital electronic health record data},
	volume = {14},
	number = {2},
	elocation-id = {e080678},
	year = {2024},
	doi = {10.1136/bmjopen-2023-080678},
	publisher = {British Medical Journal Publishing Group},
	abstract = {Objectives Analysis of routinely collected electronic health data is a key tool for long-term condition research and practice for hospitalised patients. This requires accurate and complete ascertainment of a broad range of diagnoses, something not always recorded on an admission document at a single point in time. This study aimed to ascertain how far back in time electronic hospital records need to be interrogated to capture long-term condition diagnoses.Design Retrospective observational study of routinely collected hospital electronic health record data.Setting Queen Elizabeth Hospital Birmingham (UK)-linked data held by the PIONEER acute care data hub.Participants Patients whose first recorded admission for chronic obstructive pulmonary disease (COPD) exacerbation (n=560) or acute stroke (n=2142) was between January and December 2018 and who had a minimum of 10 years of data prior to the index date.Outcome measures We identified the most common International Classification of Diseases version 10-coded diagnoses received by patients with COPD and acute stroke separately. For each diagnosis, we derived the number of patients with the diagnosis recorded at least once over the full 10-year lookback period, and then compared this with shorter lookback periods from 1 year to 9 years prior to the index admission.Results Seven of the top 10 most common diagnoses in the COPD dataset reached \&gt;90\% completeness by 6 years of lookback. Atrial fibrillation and diabetes were \&gt;90\% coded with 2{\textendash}3 years of lookback, but hypertension and asthma completeness continued to rise all the way out to 10 years of lookback. For stroke, 4 of the top 10 reached 90\% completeness by 5 years of lookback; angina pectoris was \&gt;90\% coded at 7 years and previous transient ischaemic attack completeness continued to rise out to 10 years of lookback.Conclusion A 7-year lookback captures most, but not all, common diagnoses. Lookback duration should be tailored to the conditions being studied.Data may be obtained from a third party and are not publicly available. The data that support the findings of this study are not openly available due to reasons of sensitivity. Data may be accessed on request to the HDR-UK PIONEER acute data hub on provision of permission from the PIONEER Data Trust Committee and provision of a data access agreement. Data are located in controlled access data storage at the PIONEER acute data hub.},
	issn = {2044-6055},
	URL = {https://bmjopen.bmj.com/content/14/2/e080678},
	eprint = {https://bmjopen.bmj.com/content/14/2/e080678.full.pdf},
	journal = {BMJ Open}
}

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