Problem list completeness in electronic health records: A multi-site study and assessment of success factors

Adam Wright, Allison B. McCoy, Thu Trang T Hickman, Daniel St Hilaire, Damian Borbolla, Watson A. Bowes, William G. Dixon, David Dorr, Michael Krall, Sameer Malholtra, David W. Bates, Dean F. Sittig

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

Objective: To assess problem list completeness using an objective measure across a range of sites, and to identify success factors for problem list completeness. Methods: We conducted a retrospective analysis of electronic health record data and interviews at ten healthcare organizations within the United States, United Kingdom, and Argentina who use a variety of electronic health record systems: four self-developed and six commercial. At each site, we assessed the proportion of patients who have diabetes recorded on their problem list out of all patients with a hemoglobin A1c elevation <= 7.0%, which is diagnostic of diabetes. We then conducted interviews with informatics leaders at the four highest performing sites to determine factors associated with success. Finally, we surveyed all the sites about common practices implemented at the top performing sites to determine whether there was an association between problem list management practices and problem list completeness. Results: Problem list completeness across the ten sites ranged from 60.2% to 99.4%, with a mean of 78.2%. Financial incentives, problem-oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture were identified as success factors at the four hospitals with problem list completeness at or near 90.0%. Discussion: Incomplete problem lists represent a global data integrity problem that could compromise quality of care and put patients at risk. There was a wide range of problem list completeness across the healthcare facilities. Nevertheless, some facilities have achieved high levels of problem list completeness, and it is important to better understand the factors that contribute to success to improve patient safety. Conclusion: Problem list completeness varies substantially across healthcare facilities. In our review of EHR systems at ten healthcare facilities, we identified six success factors which may be useful for healthcare organizations seeking to improve the quality of their problem list documentation: financial incentives, problem oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture.

Original languageEnglish (US)
Pages (from-to)784-790
Number of pages7
JournalInternational Journal of Medical Informatics
Volume84
Issue number10
DOIs
StatePublished - Oct 1 2015

Fingerprint

Electronic Health Records
Delivery of Health Care
Organizational Culture
Motivation
Interviews
Informatics
Quality of Health Care
Practice Management
Argentina
Patient Safety
Documentation
Hemoglobins

Keywords

  • Diabetes
  • Electronic health records
  • Problem lists
  • Quality

ASJC Scopus subject areas

  • Health Informatics

Cite this

Wright, A., McCoy, A. B., Hickman, T. T. T., Hilaire, D. S., Borbolla, D., Bowes, W. A., ... Sittig, D. F. (2015). Problem list completeness in electronic health records: A multi-site study and assessment of success factors. International Journal of Medical Informatics, 84(10), 784-790. https://doi.org/10.1016/j.ijmedinf.2015.06.011

Problem list completeness in electronic health records : A multi-site study and assessment of success factors. / Wright, Adam; McCoy, Allison B.; Hickman, Thu Trang T; Hilaire, Daniel St; Borbolla, Damian; Bowes, Watson A.; Dixon, William G.; Dorr, David; Krall, Michael; Malholtra, Sameer; Bates, David W.; Sittig, Dean F.

In: International Journal of Medical Informatics, Vol. 84, No. 10, 01.10.2015, p. 784-790.

Research output: Contribution to journalArticle

Wright, A, McCoy, AB, Hickman, TTT, Hilaire, DS, Borbolla, D, Bowes, WA, Dixon, WG, Dorr, D, Krall, M, Malholtra, S, Bates, DW & Sittig, DF 2015, 'Problem list completeness in electronic health records: A multi-site study and assessment of success factors', International Journal of Medical Informatics, vol. 84, no. 10, pp. 784-790. https://doi.org/10.1016/j.ijmedinf.2015.06.011
Wright, Adam ; McCoy, Allison B. ; Hickman, Thu Trang T ; Hilaire, Daniel St ; Borbolla, Damian ; Bowes, Watson A. ; Dixon, William G. ; Dorr, David ; Krall, Michael ; Malholtra, Sameer ; Bates, David W. ; Sittig, Dean F. / Problem list completeness in electronic health records : A multi-site study and assessment of success factors. In: International Journal of Medical Informatics. 2015 ; Vol. 84, No. 10. pp. 784-790.
@article{c048716a97aa4e428b8839c2abcb8c27,
title = "Problem list completeness in electronic health records: A multi-site study and assessment of success factors",
abstract = "Objective: To assess problem list completeness using an objective measure across a range of sites, and to identify success factors for problem list completeness. Methods: We conducted a retrospective analysis of electronic health record data and interviews at ten healthcare organizations within the United States, United Kingdom, and Argentina who use a variety of electronic health record systems: four self-developed and six commercial. At each site, we assessed the proportion of patients who have diabetes recorded on their problem list out of all patients with a hemoglobin A1c elevation <= 7.0{\%}, which is diagnostic of diabetes. We then conducted interviews with informatics leaders at the four highest performing sites to determine factors associated with success. Finally, we surveyed all the sites about common practices implemented at the top performing sites to determine whether there was an association between problem list management practices and problem list completeness. Results: Problem list completeness across the ten sites ranged from 60.2{\%} to 99.4{\%}, with a mean of 78.2{\%}. Financial incentives, problem-oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture were identified as success factors at the four hospitals with problem list completeness at or near 90.0{\%}. Discussion: Incomplete problem lists represent a global data integrity problem that could compromise quality of care and put patients at risk. There was a wide range of problem list completeness across the healthcare facilities. Nevertheless, some facilities have achieved high levels of problem list completeness, and it is important to better understand the factors that contribute to success to improve patient safety. Conclusion: Problem list completeness varies substantially across healthcare facilities. In our review of EHR systems at ten healthcare facilities, we identified six success factors which may be useful for healthcare organizations seeking to improve the quality of their problem list documentation: financial incentives, problem oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture.",
keywords = "Diabetes, Electronic health records, Problem lists, Quality",
author = "Adam Wright and McCoy, {Allison B.} and Hickman, {Thu Trang T} and Hilaire, {Daniel St} and Damian Borbolla and Bowes, {Watson A.} and Dixon, {William G.} and David Dorr and Michael Krall and Sameer Malholtra and Bates, {David W.} and Sittig, {Dean F.}",
year = "2015",
month = "10",
day = "1",
doi = "10.1016/j.ijmedinf.2015.06.011",
language = "English (US)",
volume = "84",
pages = "784--790",
journal = "International Journal of Medical Informatics",
issn = "1386-5056",
publisher = "Elsevier Ireland Ltd",
number = "10",

}

TY - JOUR

T1 - Problem list completeness in electronic health records

T2 - A multi-site study and assessment of success factors

AU - Wright, Adam

AU - McCoy, Allison B.

AU - Hickman, Thu Trang T

AU - Hilaire, Daniel St

AU - Borbolla, Damian

AU - Bowes, Watson A.

AU - Dixon, William G.

AU - Dorr, David

AU - Krall, Michael

AU - Malholtra, Sameer

AU - Bates, David W.

AU - Sittig, Dean F.

PY - 2015/10/1

Y1 - 2015/10/1

N2 - Objective: To assess problem list completeness using an objective measure across a range of sites, and to identify success factors for problem list completeness. Methods: We conducted a retrospective analysis of electronic health record data and interviews at ten healthcare organizations within the United States, United Kingdom, and Argentina who use a variety of electronic health record systems: four self-developed and six commercial. At each site, we assessed the proportion of patients who have diabetes recorded on their problem list out of all patients with a hemoglobin A1c elevation <= 7.0%, which is diagnostic of diabetes. We then conducted interviews with informatics leaders at the four highest performing sites to determine factors associated with success. Finally, we surveyed all the sites about common practices implemented at the top performing sites to determine whether there was an association between problem list management practices and problem list completeness. Results: Problem list completeness across the ten sites ranged from 60.2% to 99.4%, with a mean of 78.2%. Financial incentives, problem-oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture were identified as success factors at the four hospitals with problem list completeness at or near 90.0%. Discussion: Incomplete problem lists represent a global data integrity problem that could compromise quality of care and put patients at risk. There was a wide range of problem list completeness across the healthcare facilities. Nevertheless, some facilities have achieved high levels of problem list completeness, and it is important to better understand the factors that contribute to success to improve patient safety. Conclusion: Problem list completeness varies substantially across healthcare facilities. In our review of EHR systems at ten healthcare facilities, we identified six success factors which may be useful for healthcare organizations seeking to improve the quality of their problem list documentation: financial incentives, problem oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture.

AB - Objective: To assess problem list completeness using an objective measure across a range of sites, and to identify success factors for problem list completeness. Methods: We conducted a retrospective analysis of electronic health record data and interviews at ten healthcare organizations within the United States, United Kingdom, and Argentina who use a variety of electronic health record systems: four self-developed and six commercial. At each site, we assessed the proportion of patients who have diabetes recorded on their problem list out of all patients with a hemoglobin A1c elevation <= 7.0%, which is diagnostic of diabetes. We then conducted interviews with informatics leaders at the four highest performing sites to determine factors associated with success. Finally, we surveyed all the sites about common practices implemented at the top performing sites to determine whether there was an association between problem list management practices and problem list completeness. Results: Problem list completeness across the ten sites ranged from 60.2% to 99.4%, with a mean of 78.2%. Financial incentives, problem-oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture were identified as success factors at the four hospitals with problem list completeness at or near 90.0%. Discussion: Incomplete problem lists represent a global data integrity problem that could compromise quality of care and put patients at risk. There was a wide range of problem list completeness across the healthcare facilities. Nevertheless, some facilities have achieved high levels of problem list completeness, and it is important to better understand the factors that contribute to success to improve patient safety. Conclusion: Problem list completeness varies substantially across healthcare facilities. In our review of EHR systems at ten healthcare facilities, we identified six success factors which may be useful for healthcare organizations seeking to improve the quality of their problem list documentation: financial incentives, problem oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture.

KW - Diabetes

KW - Electronic health records

KW - Problem lists

KW - Quality

UR - http://www.scopus.com/inward/record.url?scp=84940900319&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84940900319&partnerID=8YFLogxK

U2 - 10.1016/j.ijmedinf.2015.06.011

DO - 10.1016/j.ijmedinf.2015.06.011

M3 - Article

C2 - 26228650

AN - SCOPUS:84940900319

VL - 84

SP - 784

EP - 790

JO - International Journal of Medical Informatics

JF - International Journal of Medical Informatics

SN - 1386-5056

IS - 10

ER -