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Level of accuracy of diagnoses recorded in discharge summaries: a cohort study in three respiratory wards

Level of accuracy of diagnoses recorded in discharge summaries: a cohort study in three respiratory wards
Level of accuracy of diagnoses recorded in discharge summaries: a cohort study in three respiratory wards

Rationale: One of the key functions of the discharge summary is to convey accurate diagnostic description of patients. Inaccurate or missing diagnoses may result in a false clinical picture, inappropriate management, poor quality of care, and a higher risk of re-admission. While several studies have investigated the presence or absence of diagnoses within discharge summaries, there are very few published studies assessing the accuracy of these diagnoses. The aim of this study was to measure the accuracy of diagnoses recorded in sample summaries, and to determine if it was correlated with the type of diagnoses (eg, “respiratory” diagnoses), the number of diagnoses, or the length of patient stay. Methods: A prospective cohort study was conducted in three respiratory wards in a large UK NHS Teaching Hospital. We determined the reference list of diagnoses (the closest to the true state of the patient based on consultant knowledge, patient records, and laboratory investigations) for comparison with the diagnoses recorded in a discharge summary. To enable objective comparison, all patient diagnoses were encoded using a standardized terminology (ICD-10). Inaccuracy of the primary diagnosis alone and all diagnoses in discharge summaries was measured and then correlated with type of diseases, number of diagnoses, and length of patient stay. Results: A total of 107 of 110 consecutive discharge summaries were analysed. The mean inaccuracy rate per discharge summary was 55% [95% CI 52 to 58%]. Primary diagnoses were wrong, inaccurate, missing, or mis-recorded as a secondary diagnosis in half the summaries. The inaccuracy rate was correlated with the type of disease but not with number of diagnoses nor length of patient stay. Conclusion: Our study showed that diagnoses were not accurately recorded in discharge summaries, highlighting the need to measure and improve discharge summary quality.

coding, data accuracy, diagnosis, ICD 10 coding, patient discharge summaries, quality of health care
1356-1294
1-8
Tsopra, Rosy
3741a138-0b19-4ed3-a96c-1df7338c22c1
Wyatt, Jeremy C.
8361be5a-fca9-4acf-b3d2-7ce04126f468
Beirne, Paul
962c2183-a978-4278-8866-09cfbca46928
Rodger, Kirsty
f2e4ebbe-c720-40a5-915b-fe5ed1bc77c3
Callister, Matthew
0a1d4b62-4f9e-4375-885d-ce7bdba6d73e
Ghosh, Dipansu
eb9d45b8-633c-4293-a8e2-997c00279916
Clifton, Ian J.
d5677cec-7406-4f6a-92a6-5e2b2670ba54
Whitaker, Paul
ee3c6e66-801f-4b46-aa08-e87c3eadd07d
Peckham, Daniel
e22cccc4-790e-445b-803e-9ade010384cf
Tsopra, Rosy
3741a138-0b19-4ed3-a96c-1df7338c22c1
Wyatt, Jeremy C.
8361be5a-fca9-4acf-b3d2-7ce04126f468
Beirne, Paul
962c2183-a978-4278-8866-09cfbca46928
Rodger, Kirsty
f2e4ebbe-c720-40a5-915b-fe5ed1bc77c3
Callister, Matthew
0a1d4b62-4f9e-4375-885d-ce7bdba6d73e
Ghosh, Dipansu
eb9d45b8-633c-4293-a8e2-997c00279916
Clifton, Ian J.
d5677cec-7406-4f6a-92a6-5e2b2670ba54
Whitaker, Paul
ee3c6e66-801f-4b46-aa08-e87c3eadd07d
Peckham, Daniel
e22cccc4-790e-445b-803e-9ade010384cf

Tsopra, Rosy, Wyatt, Jeremy C., Beirne, Paul, Rodger, Kirsty, Callister, Matthew, Ghosh, Dipansu, Clifton, Ian J., Whitaker, Paul and Peckham, Daniel (2018) Level of accuracy of diagnoses recorded in discharge summaries: a cohort study in three respiratory wards. Journal of Evaluation in Clinical Practice, 1-8. (doi:10.1111/jep.13020).

Record type: Article

Abstract

Rationale: One of the key functions of the discharge summary is to convey accurate diagnostic description of patients. Inaccurate or missing diagnoses may result in a false clinical picture, inappropriate management, poor quality of care, and a higher risk of re-admission. While several studies have investigated the presence or absence of diagnoses within discharge summaries, there are very few published studies assessing the accuracy of these diagnoses. The aim of this study was to measure the accuracy of diagnoses recorded in sample summaries, and to determine if it was correlated with the type of diagnoses (eg, “respiratory” diagnoses), the number of diagnoses, or the length of patient stay. Methods: A prospective cohort study was conducted in three respiratory wards in a large UK NHS Teaching Hospital. We determined the reference list of diagnoses (the closest to the true state of the patient based on consultant knowledge, patient records, and laboratory investigations) for comparison with the diagnoses recorded in a discharge summary. To enable objective comparison, all patient diagnoses were encoded using a standardized terminology (ICD-10). Inaccuracy of the primary diagnosis alone and all diagnoses in discharge summaries was measured and then correlated with type of diseases, number of diagnoses, and length of patient stay. Results: A total of 107 of 110 consecutive discharge summaries were analysed. The mean inaccuracy rate per discharge summary was 55% [95% CI 52 to 58%]. Primary diagnoses were wrong, inaccurate, missing, or mis-recorded as a secondary diagnosis in half the summaries. The inaccuracy rate was correlated with the type of disease but not with number of diagnoses nor length of patient stay. Conclusion: Our study showed that diagnoses were not accurately recorded in discharge summaries, highlighting the need to measure and improve discharge summary quality.

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More information

Accepted/In Press date: 19 July 2018
e-pub ahead of print date: 14 August 2018
Keywords: coding, data accuracy, diagnosis, ICD 10 coding, patient discharge summaries, quality of health care

Identifiers

Local EPrints ID: 426592
URI: https://eprints.soton.ac.uk/id/eprint/426592
ISSN: 1356-1294
PURE UUID: d36cd98f-fb2a-4756-a2e4-cfdd119a46bc
ORCID for Jeremy C. Wyatt: ORCID iD orcid.org/0000-0001-7008-1473

Catalogue record

Date deposited: 30 Nov 2018 17:30
Last modified: 20 Jul 2019 00:33

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