Aarhus University Seal / Aarhus Universitets segl

Good organizational reasons for better medical records: The data work of clinical documentation integrity specialists

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Standard

Good organizational reasons for better medical records : The data work of clinical documentation integrity specialists. / Pine, Kathleen H.; Bossen, Claus.

In: Big Data and Society, Vol. 7, No. 2, 10.2020.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

APA

CBE

MLA

Vancouver

Author

Bibtex

@article{1b44d4db2d294fc8873d48545186e5c8,
title = "Good organizational reasons for better medical records: The data work of clinical documentation integrity specialists",
abstract = "Healthcare organizations and workers are under pressure to produce increasingly complete and accurate data for multiple data-intensive endeavors. However, little research has examined the emerging occupations arising to carry out the data work necessary to produce “improved” data sets, or the specific work activities of these emerging data occupations. We describe the work of Clinical Documentation Integrity Specialists (CDIS), an emerging occupation that focuses on improving clinical documentation to produce more detailed and accurate administrative datasets crucial for evolving data-intensive forms of healthcare accountability, management, and research. Using ethnographic methods, we describe the core of CDIS{\textquoteright} work as a translation practice in which the language, interests, and concerns of clinicians and clinical documentation are translated via real-time “nudging” and ongoing education of clinicians into the language, interests, and concerns of medical coders, structured administrative datasets, and the various stakeholders of these datasets. Further, we show how the institutional context of CDIS{\textquoteright} work shapes the occupational virtues that guide CDIS{\textquoteright} translation practice, including financial reimbursement, quality measures, clinical accuracy, and protecting clinician{\textquoteright}s time. Despite the existence of these multiple virtues, financial reimbursement is the most prominent virtue guiding CDIS{\textquoteright} limited attention. Thus, overall clinical documentation is “improved” in specific, partial ways. This research provides one of the first studies of the emergent data work occupations arising in the wake of digitization and big data opportunities, and shows how local data settings shape large scale data in specific ways and thus may influence outcomes of analyses based on such data.",
keywords = "big data, Clinical documentation improvement specialists, data work, emerging occupations, healthcare, ICD-10",
author = "Pine, {Kathleen H.} and Claus Bossen",
year = "2020",
month = oct,
doi = "10.1177/2053951720965616",
language = "English",
volume = "7",
journal = "Big Data & Society",
issn = "2053-9517",
publisher = ": SAGE Publications ",
number = "2",

}

RIS

TY - JOUR

T1 - Good organizational reasons for better medical records

T2 - The data work of clinical documentation integrity specialists

AU - Pine, Kathleen H.

AU - Bossen, Claus

PY - 2020/10

Y1 - 2020/10

N2 - Healthcare organizations and workers are under pressure to produce increasingly complete and accurate data for multiple data-intensive endeavors. However, little research has examined the emerging occupations arising to carry out the data work necessary to produce “improved” data sets, or the specific work activities of these emerging data occupations. We describe the work of Clinical Documentation Integrity Specialists (CDIS), an emerging occupation that focuses on improving clinical documentation to produce more detailed and accurate administrative datasets crucial for evolving data-intensive forms of healthcare accountability, management, and research. Using ethnographic methods, we describe the core of CDIS’ work as a translation practice in which the language, interests, and concerns of clinicians and clinical documentation are translated via real-time “nudging” and ongoing education of clinicians into the language, interests, and concerns of medical coders, structured administrative datasets, and the various stakeholders of these datasets. Further, we show how the institutional context of CDIS’ work shapes the occupational virtues that guide CDIS’ translation practice, including financial reimbursement, quality measures, clinical accuracy, and protecting clinician’s time. Despite the existence of these multiple virtues, financial reimbursement is the most prominent virtue guiding CDIS’ limited attention. Thus, overall clinical documentation is “improved” in specific, partial ways. This research provides one of the first studies of the emergent data work occupations arising in the wake of digitization and big data opportunities, and shows how local data settings shape large scale data in specific ways and thus may influence outcomes of analyses based on such data.

AB - Healthcare organizations and workers are under pressure to produce increasingly complete and accurate data for multiple data-intensive endeavors. However, little research has examined the emerging occupations arising to carry out the data work necessary to produce “improved” data sets, or the specific work activities of these emerging data occupations. We describe the work of Clinical Documentation Integrity Specialists (CDIS), an emerging occupation that focuses on improving clinical documentation to produce more detailed and accurate administrative datasets crucial for evolving data-intensive forms of healthcare accountability, management, and research. Using ethnographic methods, we describe the core of CDIS’ work as a translation practice in which the language, interests, and concerns of clinicians and clinical documentation are translated via real-time “nudging” and ongoing education of clinicians into the language, interests, and concerns of medical coders, structured administrative datasets, and the various stakeholders of these datasets. Further, we show how the institutional context of CDIS’ work shapes the occupational virtues that guide CDIS’ translation practice, including financial reimbursement, quality measures, clinical accuracy, and protecting clinician’s time. Despite the existence of these multiple virtues, financial reimbursement is the most prominent virtue guiding CDIS’ limited attention. Thus, overall clinical documentation is “improved” in specific, partial ways. This research provides one of the first studies of the emergent data work occupations arising in the wake of digitization and big data opportunities, and shows how local data settings shape large scale data in specific ways and thus may influence outcomes of analyses based on such data.

KW - big data

KW - Clinical documentation improvement specialists

KW - data work

KW - emerging occupations

KW - healthcare

KW - ICD-10

UR - http://www.scopus.com/inward/record.url?scp=85092897836&partnerID=8YFLogxK

U2 - 10.1177/2053951720965616

DO - 10.1177/2053951720965616

M3 - Journal article

AN - SCOPUS:85092897836

VL - 7

JO - Big Data & Society

JF - Big Data & Society

SN - 2053-9517

IS - 2

ER -