Computer-generated structured electronic medical records are preferable to conventional medical records for patients with acute abdominal pain: a prospective, double-blinded study

Leena Saaristo; Mika T. Ukkonen; Erkki Ville Wirta; Sannamari Kotaluoto; Matleena Lammi; Johanna M. Laukkarinen; Satu Liisa K. Pauniaho

doi:10.1007/s10916-022-01852-w

Computer-generated structured electronic medical records are preferable to conventional medical records for patients with acute abdominal pain: a prospective, double-blinded study

Leena Saaristo, Mika T. Ukkonen, Erkki Ville Wirta, Sannamari Kotaluoto, Matleena Lammi, Johanna M. Laukkarinen, Satu Liisa K. Pauniaho

Research output: Contribution to journal › Article › Scientific › peer-review

4 Downloads (Pure)

Abstract

Objectives: Structured medical records improve readability and ensure the inclusion of information necessary for correct diagnosis and treatment. This is the first study to assess the quality of computer-generated structured medical records by comparing them to conventional medical records on patients with acute abdominal pain. Materials and methods: A prospective double-blinded study was conducted in a tertiary referral center emergency department between January 2018 and June 2018. Patients were examined by emergency department physicians and by experience and inexperienced researcher. The researchers used a new electronical medical records system, which gathered data during the examination and the system generate structured medical records containing natural language. Conventional medical records dictated by physician and computer-generated medical records were compared by a group of independent clinicians. Results: Ninety-nine patients were included. The overall quality of the computer-generated medical records was better than the quality of conventional human-generated medical records – the structure was similar or better in 99% of cases and the readability was similar or better in 86% of cases, p < 0.001. The quality of medical history, current illness, and findings of physical examinations were likewise better with the computer-generated recording. The results were similar when patients were examined by experienced or inexperienced researcher using the computer-generated recording. Discussion: The quality of computer-generated structured medical records was superior to that of conventional medical records. The quality remained similar regardless of the researcher’s level of experience. The system allows automatic risk scoring and easy access for quality control of patient care. We therefore consider that it would be useful in wider practice.

Original language	English
Article number	63
Number of pages	7
Journal	Journal of Medical Systems
Volume	46
Issue number	10
DOIs	https://doi.org/10.1007/s10916-022-01852-w
Publication status	Published - 2022
Publication type	A1 Journal article-refereed

Keywords

Abdominal pain
Medical records
Medical Records Systems, Computerized
Quality of Health Care

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

Medicine (miscellaneous)
Information Systems
Health Informatics
Health Information Management

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/s10916-022-01852-wLicence: CC BY

s10916-022-01852-wFinal published version, 989 KBLicence: CC BY

https://urn.fi/URN:NBN:fi:tuni-202209197133Licence: CC BY

Cite this

Saaristo, L., Ukkonen, M. T., Wirta, E. V., Kotaluoto, S., Lammi, M., Laukkarinen, J. M., & Pauniaho, S. L. K. (2022). Computer-generated structured electronic medical records are preferable to conventional medical records for patients with acute abdominal pain: a prospective, double-blinded study. Journal of Medical Systems, 46(10), Article 63. https://doi.org/10.1007/s10916-022-01852-w

@article{4be6720c3301471199e64ad2ee70879f,

title = "Computer-generated structured electronic medical records are preferable to conventional medical records for patients with acute abdominal pain: a prospective, double-blinded study",

abstract = "Objectives: Structured medical records improve readability and ensure the inclusion of information necessary for correct diagnosis and treatment. This is the first study to assess the quality of computer-generated structured medical records by comparing them to conventional medical records on patients with acute abdominal pain. Materials and methods: A prospective double-blinded study was conducted in a tertiary referral center emergency department between January 2018 and June 2018. Patients were examined by emergency department physicians and by experience and inexperienced researcher. The researchers used a new electronical medical records system, which gathered data during the examination and the system generate structured medical records containing natural language. Conventional medical records dictated by physician and computer-generated medical records were compared by a group of independent clinicians. Results: Ninety-nine patients were included. The overall quality of the computer-generated medical records was better than the quality of conventional human-generated medical records – the structure was similar or better in 99% of cases and the readability was similar or better in 86% of cases, p < 0.001. The quality of medical history, current illness, and findings of physical examinations were likewise better with the computer-generated recording. The results were similar when patients were examined by experienced or inexperienced researcher using the computer-generated recording. Discussion: The quality of computer-generated structured medical records was superior to that of conventional medical records. The quality remained similar regardless of the researcher{\textquoteright}s level of experience. The system allows automatic risk scoring and easy access for quality control of patient care. We therefore consider that it would be useful in wider practice.",

keywords = "Abdominal pain, Medical records, Medical Records Systems, Computerized, Quality of Health Care",

author = "Leena Saaristo and Ukkonen, {Mika T.} and Wirta, {Erkki Ville} and Sannamari Kotaluoto and Matleena Lammi and Laukkarinen, {Johanna M.} and Pauniaho, {Satu Liisa K.}",

note = "Funding Information: The authors would like to thank Cinia Ltd, Finland for design and development of the system. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

doi = "10.1007/s10916-022-01852-w",

language = "English",

volume = "46",

journal = "Journal of Medical Systems",

issn = "0148-5598",

publisher = "Springer Verlag",

number = "10",

}

Saaristo, L, Ukkonen, MT, Wirta, EV, Kotaluoto, S, Lammi, M, Laukkarinen, JM & Pauniaho, SLK 2022, 'Computer-generated structured electronic medical records are preferable to conventional medical records for patients with acute abdominal pain: a prospective, double-blinded study', Journal of Medical Systems, vol. 46, no. 10, 63. https://doi.org/10.1007/s10916-022-01852-w

Computer-generated structured electronic medical records are preferable to conventional medical records for patients with acute abdominal pain: a prospective, double-blinded study. / Saaristo, Leena; Ukkonen, Mika T.; Wirta, Erkki Ville et al.
In: Journal of Medical Systems, Vol. 46, No. 10, 63, 2022.

Research output: Contribution to journal › Article › Scientific › peer-review

TY - JOUR

T1 - Computer-generated structured electronic medical records are preferable to conventional medical records for patients with acute abdominal pain

T2 - a prospective, double-blinded study

AU - Saaristo, Leena

AU - Ukkonen, Mika T.

AU - Wirta, Erkki Ville

AU - Kotaluoto, Sannamari

AU - Lammi, Matleena

AU - Laukkarinen, Johanna M.

AU - Pauniaho, Satu Liisa K.

PY - 2022

Y1 - 2022

N2 - Objectives: Structured medical records improve readability and ensure the inclusion of information necessary for correct diagnosis and treatment. This is the first study to assess the quality of computer-generated structured medical records by comparing them to conventional medical records on patients with acute abdominal pain. Materials and methods: A prospective double-blinded study was conducted in a tertiary referral center emergency department between January 2018 and June 2018. Patients were examined by emergency department physicians and by experience and inexperienced researcher. The researchers used a new electronical medical records system, which gathered data during the examination and the system generate structured medical records containing natural language. Conventional medical records dictated by physician and computer-generated medical records were compared by a group of independent clinicians. Results: Ninety-nine patients were included. The overall quality of the computer-generated medical records was better than the quality of conventional human-generated medical records – the structure was similar or better in 99% of cases and the readability was similar or better in 86% of cases, p < 0.001. The quality of medical history, current illness, and findings of physical examinations were likewise better with the computer-generated recording. The results were similar when patients were examined by experienced or inexperienced researcher using the computer-generated recording. Discussion: The quality of computer-generated structured medical records was superior to that of conventional medical records. The quality remained similar regardless of the researcher’s level of experience. The system allows automatic risk scoring and easy access for quality control of patient care. We therefore consider that it would be useful in wider practice.

AB - Objectives: Structured medical records improve readability and ensure the inclusion of information necessary for correct diagnosis and treatment. This is the first study to assess the quality of computer-generated structured medical records by comparing them to conventional medical records on patients with acute abdominal pain. Materials and methods: A prospective double-blinded study was conducted in a tertiary referral center emergency department between January 2018 and June 2018. Patients were examined by emergency department physicians and by experience and inexperienced researcher. The researchers used a new electronical medical records system, which gathered data during the examination and the system generate structured medical records containing natural language. Conventional medical records dictated by physician and computer-generated medical records were compared by a group of independent clinicians. Results: Ninety-nine patients were included. The overall quality of the computer-generated medical records was better than the quality of conventional human-generated medical records – the structure was similar or better in 99% of cases and the readability was similar or better in 86% of cases, p < 0.001. The quality of medical history, current illness, and findings of physical examinations were likewise better with the computer-generated recording. The results were similar when patients were examined by experienced or inexperienced researcher using the computer-generated recording. Discussion: The quality of computer-generated structured medical records was superior to that of conventional medical records. The quality remained similar regardless of the researcher’s level of experience. The system allows automatic risk scoring and easy access for quality control of patient care. We therefore consider that it would be useful in wider practice.

KW - Abdominal pain

KW - Medical records

KW - Medical Records Systems, Computerized

KW - Quality of Health Care

U2 - 10.1007/s10916-022-01852-w

DO - 10.1007/s10916-022-01852-w

M3 - Article

C2 - 36008740

AN - SCOPUS:85137127187

SN - 0148-5598

VL - 46

JO - Journal of Medical Systems

JF - Journal of Medical Systems

IS - 10

M1 - 63

ER -

Computer-generated structured electronic medical records are preferable to conventional medical records for patients with acute abdominal pain: a prospective, double-blinded study

Abstract

Keywords

Publication forum classification

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Cite this