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The Work and Workers of Centering Patients in Quality Improvement Networks
The Work and Workers of Centering Patients in Quality Improvement Networks
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202103643
- ISBN
- 9798314874332
- DDC
- 614
- 서명/저자
- The Work and Workers of Centering Patients in Quality Improvement Networks
- 발행사항
- [Sl] : University of Michigan, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 147 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-11, Section: B.
- 주기사항
- Advisor: Singh, Karandeep;Vinson, Alexandra Hope.
- 학위논문주기
- Thesis (Ph.D.)--University of Michigan, 2025.
- 초록/해제
- 요약Quality Improvement Networks (QINs) are an emerging type of healthcare organization that operate at the network level and use a Learning Health Systems (LHS) approach: QINs connect health systems over large areas with the goal of improving patient health outcomes by learning from patient data. To do this work, QINs collect patient data, implement quality improvement (QI) initiatives to standardize care, and connect stakeholders to share resources. QINs do not provide direct care, but they do aim to improve patient care. Improving patient care through patient-centered means is the basis for an LHS approach. While methods for centering patients on the level of the health system are well established, on the network level at which QINs operate, they are not. My data comes from ethnographic observation of QINs and aims to identify how people within them understand the patients they seek to serve. The study was conducted over a period of one year during which I observed three QINs in a midwestern state. I attended a variety of QIN meetings including operational meetings, data manager meetings, and QIN conferences. I also conducted over 50 interviews with QIN stakeholders such as physicians, data abstractors, and patient advocates. Based on inductive qualitative analysis, I find that QINs use a combination of data abstraction, direct patient engagement, and a variety of indirect methods to understand patients. Much of this work to understand patients relies on a central, but understudied group of QIN staff: data workers. Data workers complete the foundational work of data abstraction though transcribing clinical data into centralized QIN databases. I find that data workers also conduct data analysis and implement QI initiatives while facing pressures ranging from clinical demands to outsourcing. As data work continues to expand to support LHSs at network-level scales, the multi-faceted world of the data worker that I present suggests that the contributions of these workers are important beyond their named role. Although QINs do not provide patient care, they do engage patient advocates directly to gain insight into their care and feedback on patient educational materials. QINs use a variety of methods to understand patients' health outcomes and experiences. I describe how patient advocates become engaged in QINs, barriers to engagement, and activities of these patients. I also find that patients act as cheerleaders to motivate physicians to continue QI work. As efforts to build LHSs at ever larger scales continue to grow, the experiences I highlight show how patient engagement occurs at the network level. Finally, I describe the activities in which QINs engage to understand patients that do not involve direct patient contact. I find that QINs use indirect means such as data abstraction and analysis to understand patient health outcomes. Additionally, quality improvement-focused work and activities outside of the context of QINs provide invaluable insight into the QINs' understanding of the logistical and emotional aspects of patient experience. As network-level organizations, QINs are situated far from the patients they ultimately serve. They therefore employ many strategies to center patients including data abstraction, direct patient engagement, and various indirect methods of data collection. While centering patients is a core value of the LHS approach, I elucidate the extent to which this value is actually adhered to at the network level as well as the work and workers involved in achieving this.
- 일반주제명
- Health sciences
- 일반주제명
- Medicine
- 키워드
- Data workers
- 기타저자
- University of Michigan Hlth Infrastr & Lrng Systs PhD
- 기본자료저록
- Dissertations Abstracts International. 86-11B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■1001 ▼aBrannon, Elliott.
■24510▼aThe Work and Workers of Centering Patients in Quality Improvement Networks
■260 ▼a[Sl]▼bUniversity of Michigan▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a147 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-11, Section: B.
■500 ▼aAdvisor: Singh, Karandeep;Vinson, Alexandra Hope.
■5021 ▼aThesis (Ph.D.)--University of Michigan, 2025.
■520 ▼aQuality Improvement Networks (QINs) are an emerging type of healthcare organization that operate at the network level and use a Learning Health Systems (LHS) approach: QINs connect health systems over large areas with the goal of improving patient health outcomes by learning from patient data. To do this work, QINs collect patient data, implement quality improvement (QI) initiatives to standardize care, and connect stakeholders to share resources. QINs do not provide direct care, but they do aim to improve patient care. Improving patient care through patient-centered means is the basis for an LHS approach. While methods for centering patients on the level of the health system are well established, on the network level at which QINs operate, they are not. My data comes from ethnographic observation of QINs and aims to identify how people within them understand the patients they seek to serve. The study was conducted over a period of one year during which I observed three QINs in a midwestern state. I attended a variety of QIN meetings including operational meetings, data manager meetings, and QIN conferences. I also conducted over 50 interviews with QIN stakeholders such as physicians, data abstractors, and patient advocates. Based on inductive qualitative analysis, I find that QINs use a combination of data abstraction, direct patient engagement, and a variety of indirect methods to understand patients. Much of this work to understand patients relies on a central, but understudied group of QIN staff: data workers. Data workers complete the foundational work of data abstraction though transcribing clinical data into centralized QIN databases. I find that data workers also conduct data analysis and implement QI initiatives while facing pressures ranging from clinical demands to outsourcing. As data work continues to expand to support LHSs at network-level scales, the multi-faceted world of the data worker that I present suggests that the contributions of these workers are important beyond their named role. Although QINs do not provide patient care, they do engage patient advocates directly to gain insight into their care and feedback on patient educational materials. QINs use a variety of methods to understand patients' health outcomes and experiences. I describe how patient advocates become engaged in QINs, barriers to engagement, and activities of these patients. I also find that patients act as cheerleaders to motivate physicians to continue QI work. As efforts to build LHSs at ever larger scales continue to grow, the experiences I highlight show how patient engagement occurs at the network level. Finally, I describe the activities in which QINs engage to understand patients that do not involve direct patient contact. I find that QINs use indirect means such as data abstraction and analysis to understand patient health outcomes. Additionally, quality improvement-focused work and activities outside of the context of QINs provide invaluable insight into the QINs' understanding of the logistical and emotional aspects of patient experience. As network-level organizations, QINs are situated far from the patients they ultimately serve. They therefore employ many strategies to center patients including data abstraction, direct patient engagement, and various indirect methods of data collection. While centering patients is a core value of the LHS approach, I elucidate the extent to which this value is actually adhered to at the network level as well as the work and workers involved in achieving this.
■590 ▼aSchool code: 0127.
■650 4▼aHealth sciences
■650 4▼aMedicine
■653 ▼aQuality improvement
■653 ▼aLearning health systems
■653 ▼aPatient-centered care
■653 ▼aData workers
■690 ▼a0566
■690 ▼a0769
■690 ▼a0564
■690 ▼a0624
■71020▼aUniversity of Michigan▼bHlth Infrastr & Lrng Systs PhD.
■7730 ▼tDissertations Abstracts International▼g86-11B.
■790 ▼a0127
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17358097▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
