Download PDF
Appl Clin Inform 2020; 11(04): 635-643
DOI: 10.1055/s-0040-1715895
Research Article

Clinical Decision Support for Worker Health: A Five-Site Qualitative Needs Assessment in Primary Care Settings

Joan S. Ash
1   Department of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon Health & Science University, Portland, Oregon, United States
,
Dian Chase
1   Department of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon Health & Science University, Portland, Oregon, United States
,
Sherry Baron
2   Department of Urban Studies, Barry Commoner Center for Health and the Environment, Queens College, City University of New York, New York, New York, United States
,
Margaret S. Filios
3   National Institute for Occupational Safety and Health/Centers for Disease Control and Prevention, Cincinnati, Ohio and Morgantown, West Virginia, United States
,
Richard N. Shiffman
4   Yale Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut, United States
,
Stacey Marovich
3   National Institute for Occupational Safety and Health/Centers for Disease Control and Prevention, Cincinnati, Ohio and Morgantown, West Virginia, United States
,
Jane Wiesen
1   Department of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon Health & Science University, Portland, Oregon, United States
,
Genevieve B. Luensman
3   National Institute for Occupational Safety and Health/Centers for Disease Control and Prevention, Cincinnati, Ohio and Morgantown, West Virginia, United States
› Author Affiliations Funding This project was supported by CDC/NIOSH Contract 200–2015–61837 as part of NORA project no.: 927ZLDN. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.
› Further Information
Also available at
   Permissions and Reprints

Abstract

Background Although patients who work and have related health issues are usually first seen in primary care, providers in these settings do not routinely ask questions about work. Guidelines to help manage such patients are rarely used in primary care. Electronic health record (EHR) systems with worker health clinical decision support (CDS) tools have potential for assisting these practices.

Objective This study aimed to identify the need for, and barriers and facilitators related to, implementation of CDS tools for the clinical management of working patients in a variety of primary care settings.

Methods We used a qualitative design that included analysis of interview transcripts and observational field notes from 10 clinics in five organizations.

Results We interviewed 83 providers, staff members, managers, informatics and information technology experts, and leaders and spent 35 hours observing. We identified eight themes in four categories related to CDS for worker health (operational issues, usefulness of proposed CDS, effort and time-related issues, and topic-specific issues). These categories were classified as facilitators or barriers to the use of the CDS tools. Facilitators related to operational issues include current technical feasibility and new work patterns associated with the coordinated care model. Facilitators concerning usefulness include users' need for awareness and evidence-based tools, appropriateness of the proposed CDS for their patients, and the benefits of population health data. Barriers that are effort-related include additional time this proposed CDS might take, and other pressing organizational priorities. Barriers that are topic-specific include sensitive issues related to health and work and the complexities of information about work.

Conclusion We discovered several themes not previously described that can guide future CDS development: technical feasibility of the proposed CDS within commercial EHRs, the sensitive nature of some CDS content, and the need to assist the entire health care team in managing worker health.

Keywords

attitude to computers - hospital information systems - physician order entry - clinical decision support - occupational health

Protection of Human and Animal Subjects

This study was approved by the Institutional Review Boards (IRBs) at NIOSH, Oregon Health & Science University (OHSU), and two of our study sites. IRB waivers and/or official determinations (if a site did not have an IRB, it had other mechanisms for reviewing our protocol) were also obtained from the other three sites.


Supplementary Material



Publication History

Received: 18 May 2020

Accepted: 27 July 2020

Article published online:
30 September 2020

© 2020. Thieme. All rights reserved.

Georg Thieme Verlag KG
Stuttgart · New York

 

  • References

  • 1 Goldman RH, Peters JM. The occupational and environmental health history. JAMA 1981; 246 (24) 2831-2836
    CrossrefPubMedGoogle Scholar
  • 2 Shofer S, Haus BM, Kuschner WG. Quality of occupational history assessments in working age adults with newly diagnosed asthma. Chest 2006; 130 (02) 455-462
    CrossrefPubMedGoogle Scholar
  • 3 Politi BJ, Arena VC, Schwerha J, Sussman N. Occupational medical history taking: how are today's physicians doing? A cross-sectional investigation of the frequency of occupational history taking by physicians in a major US teaching center. J Occup Environ Med 2004; 46 (06) 550-555
    CrossrefPubMedGoogle Scholar
  • 4 Mazurek JM, Storey E. Physician-patient communication regarding asthma and work. Am J Prev Med 2012; 43 (01) 72-75
    CrossrefPubMedGoogle Scholar
  • 5 Mazurek JM, White GE, Moorman JE, Storey E. Patient-physician communication about work-related asthma: what we do and do not know. Ann Allergy Asthma Immunol 2015; 114 (02) 97-102
    CrossrefPubMedGoogle Scholar
  • 6 Newman LS. Occupational illness. N Engl J Med 1995; 333 (17) 1128-1134
    CrossrefPubMedGoogle Scholar
  • 7 Lomotan EA, Hoeksema LJ, Edmonds DE, Ramírez-Garnica G, Shiffman RN, Horwitz LI. Evaluating the use of a computerized clinical decision support system for asthma by pediatric pulmonologists. Int J Med Inform 2012; 81 (03) 157-165
    CrossrefPubMedGoogle Scholar
  • 8 Institute of Medicine. Wegman DH, Liverman CT, Schultz AM, Strawbridge LM. , eds. Incorporating occupational information in electronic health records: Letter report. Washington, DC: the Academic Press; 2011
    Google Scholar
  • 9 Shiffman RN, Michel G, Essaihi A, Thornquist E. Bridging the guideline implementation gap: a systematic, document-centered approach to guideline implementation. J Am Med Inform Assoc 2004; 11 (05) 418-426
    CrossrefPubMedGoogle Scholar
  • 10 Shiffman RN, Michel G, Rosenfeld RM, Davidson C. Building better guidelines with BRIDGE-Wiz: development and evaluation of a software assistant to promote clarity, transparency, and implementability. J Am Med Inform Assoc 2012; 19 (01) 94-101
    CrossrefPubMedGoogle Scholar
  • 11 Filios MS, Storey E, Baron S, Luensman GB, Shiffman RN. Enhancing worker health through clinical decision support (CDS): An introduction to a compilation. J Occup Environ Med 2017; 59 (11) e227-e230
    CrossrefPubMedGoogle Scholar
  • 12 Baron S, Filios MS, Marovich S, Chase D, Ash JS. Recognition of the relationship between patients' work and health: A qualitative evaluation of the need for clinical decision support for worker health I five primary care practices. J Occup Environ Med 2017; 59 (11) e245-e250
    CrossrefPubMedGoogle Scholar
  • 13 Harber P, Redlich CA, Hines S, Filios MS, Storey E. Recommendations for a clinical decision support system for work related asthma in primary care settings. J Occup Environ Med 2017; 59 (11) e231-e235
    CrossrefPubMedGoogle Scholar
  • 14 Allen A, Welch L, Kirkland K, Trout D, Baron S. Development of a diabetes mellitus knowledge resource for clinical decision support— assisting primary care physicians with work-related issues. J Occup Environ Med 2017; 59 (11) e236-e239
    CrossrefPubMedGoogle Scholar
  • 15 McLellan RK, Haas NS, Kownacki RP, Pransky GS, Talmage JB, Dreger M. Using electronic health records and clinical decision support to provide return-to-work guidance for primary care practitioners for patients with low back pain. J Occup Environ Med 2017; 59 (11) e240-e244
    CrossrefPubMedGoogle Scholar
  • 16 Ash JS, Sittig DF, McMullen CK. , et al. Studying the vendor perspective on clinical decision support. AMIA Annu Symp Proc 2011; 2011: 80-87
    PubMedGoogle Scholar
  • 17 Beebe J. Rapid Assessment Process: An Introduction. Walnut Creek, CA: Alta Mira Press; 2001
    Google Scholar
  • 18 McMullen CK, Ash JS, Sittig DF. , et al. Rapid assessment of clinical information systems in the healthcare setting: an efficient method for time-pressed evaluation. Methods Inf Med 2011; 50 (04) 299-307
    Article in Thieme ConnectPubMedGoogle Scholar
  • 19 Ash JS, Sittig DF, McMullen CK, Guappone K, Dykstra R, Carpenter J. A rapid assessment process for clinical informatics interventions. AMIA Annu Symp Proc 2008; 2008: 26-30
    PubMedGoogle Scholar
  • 20 Ash JS, Chase D, Wiesen JF, Murphy EV, Marovich S. Studying readiness for clinical decision support using the rapid assessment process and mixed methods interviews. AMIA Annu Symp Proc 2017; 2016: 285-294
    PubMedGoogle Scholar
  • 21 Ash JS, Baron S, Chase D, Filios M, Luensman G, Marovich S, Murphy E, McCormack J, Shiffman RN, Wiesen J. Clinical Decision Support for Worker Health Qualitative Study Final Report to NIOSH. 2016
    PubMedGoogle Scholar
  • 22 Crabtree BF, Miller WL. , eds. Doing Qualitative Research. 2nd ed. Thousand Oaks, CA: Sage Publications; 1999
    Google Scholar
  • 23 Berg BL, Lune H. Qualitative Research Methods for the Social Sciences. 8th ed. Boston, MA: Pearson; 2012
    Google Scholar
  • 24 Mellis C. Evidence-based medicine: what has happened in the past 50 years?. J Paediatr Child Health 2015; 51 (01) 65-68
    CrossrefPubMedGoogle Scholar
  • 25 Lulin Z, Yiranbon E, Asante Antwi H. Complementarity of clinician judgement and evidence based models in medical decision making: antecedents, prospects, and challenges. BioMed Res Int 2016; 2016: 1425693
    CrossrefPubMedGoogle Scholar
  • 26 Schaeffer C, Booton L, Halleck J, Studeny J, Coustasse A. Big data management in U.S. hospitals. Health Care Manag (Frederick) 2017; 36 (01) 87-95
    CrossrefPubMedGoogle Scholar
  • 27 Kilsdonk E, Peute LWP, Knijnenburg SL, Jaspers MWM. Factors known to influence acceptance of clinical decision support systems. Stud Health Technol Inform 2011; 169: 150-154
    PubMedGoogle Scholar
  • 28 Mamykina L, Vawdrey DK, Hripcsak G. How do residents spend their shift time? A time and motion study with a particular focus on the use of computers. Acad Med 2016; 91 (06) 827-832
    CrossrefPubMedGoogle Scholar
  • 29 Azaroff LS, Davis LK, Naparstek R, Hashimoto D, Laing JR, Wegman DH. Barriers to use of workers' compensation for patient care at Massachusetts community health centers. Health Serv Res 2013; 48 (04) 1375-1392
    CrossrefPubMedGoogle Scholar
  • 30 Schwarzer R, Cone JE, Li J, Bowler RM. A PTSD symptoms trajectory mediates between exposure levels and emotional support in police responders to 9/11: a growth curve analysis. BMC Psychiatry 2016; 16: 201
    CrossrefPubMedGoogle Scholar
  • 31 Harris DA, Mainardi A, Iyamu O. , et al. Improving the asthma disparity gap with legal advocacy? A qualitative study of patient-identified challenges to improve social and environmental factors that contribute to poorly controlled asthma. J Asthma 2018; 55 (08) 924-932
    CrossrefPubMedGoogle Scholar
  • 32 Laney AS, Blackley DJ, Halldin CN. Radiographic disease progression in contemporary US coal miners with progressive massive fibrosis. Occup Environ Med 2017; 74 (07) 517-520
    CrossrefPubMedGoogle Scholar
  • 33 Centers for Disease Control and Prevention. Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). Accessed September 3, 2019 at https://www.cdc.gov/phin/tools/phinvads/
    PubMed
  • 34 HL7 EHRS-FM Release 2 Functional Profile: Work and Health, Release 1, U.S. Realm. Accessed September 3, 2019 at: http://www.hl7.org/implement/standards/product_brief.cfm?product_id=498
    PubMed
  • 35 Wright A, Sittig DF, Ash JS, Sharma S, Pang JE, Middleton B. Clinical decision support capabilities of commercially-available clinical information systems. J Am Med Inform Assoc 2009; 16 (05) 637-644
    CrossrefPubMedGoogle Scholar
  • 36 Wright A, Ash JS, Erickson JL. , et al. A qualitative study of the activities performed by people involved in clinical decision support: recommended practices for success. J Am Med Inform Assoc 2014; 21 (03) 464-472
    CrossrefPubMedGoogle Scholar
  • 37 Revere D, Hills RH, Dixon BE, Gibson PJ, Grannis SJ. Notifiable condition reporting practices: implications for public health agency participation in a health information exchange. BMC Public Health 2017; 17 (01) 247
    CrossrefPubMedGoogle Scholar