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He W, Chima S, Emery J, Manski-Nankervis JA, Williams I, Hunter B, Nelson C, Martinez-Gutierrez J. Perceptions of primary care patients on the use of electronic clinical decision support tools to facilitate health care: A systematic review. PATIENT EDUCATION AND COUNSELING 2024; 125:108290. [PMID: 38714007 DOI: 10.1016/j.pec.2024.108290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 04/04/2024] [Accepted: 04/10/2024] [Indexed: 05/09/2024]
Abstract
OBJECTIVE Electronic clinical decision support tools (eCDSTs) are interventions designed to facilitate clinical decision-making using targeted medical knowledge and patient information. While eCDSTs have been demonstrated to improve quality of care, there is a paucity of research relating to the acceptability of eCDSTs in primary care from the patients' perspective. This study aims to summarize current evidence relating to primary care patients' perceptions and experiences on the use of eCDSTs by their clinician to provide care. METHODS Four databases (Medline, Embase, CINAHL and Cochrane Library) were searched for qualitative and quantitative studies with outcomes relating to patients' perceptions of the use of clinician-facing or shared-eCDSTs. Data extraction and critical appraisal using the Johanna Briggs Institute Critical Appraisal checklists were carried out independently by reviewers. Qualitative and quantitative outcomes were synthesized independently. We used Richardson et al. 'Patient Evaluation of Artificial Intelligence (AI) in Healthcare' framework for qualitative analysis. FINDINGS 20 papers were included for synthesis. eCDSTs were generally well-regarded by patients. The key facilitators for use were promoting informed decision-making, prompting discussions, aiding clinical decision-making, and enabling information sharing. Key barriers for use were lack of holistic care, 'medicalized' language, and confidentiality concerns. CONCLUSION Our study identified important aspects to consider in the development of future eCDSTs. Patients were generally positive regarding the use of eCDSTs; however, patient's perspectives should be included from the conception of new eCDSTs to ensure recommendations align with the needs of patients and clinicians. PRACTICE IMPLICATIONS The study results contribute to ensuring the acceptability of eCDSTs for patients and their unique needs. Encouragement is given for future development to adopt and build upon these findings. Additional research focusing on patients' perceptions of using eCDSTs for specific health conditions is deemed necessary.
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Affiliation(s)
- William He
- Department of General Practice and Primary Care, The University of Melbourne, Melbourne, Australia
| | - Sophie Chima
- Department of General Practice and Primary Care, The University of Melbourne, Melbourne, Australia; Centre for Cancer Research, University of Melbourne, Melbourne, Australia
| | - Jon Emery
- Department of General Practice and Primary Care, The University of Melbourne, Melbourne, Australia; Centre for Cancer Research, University of Melbourne, Melbourne, Australia; The Primary Care Unit, University of Cambridge, Cambridge, UK
| | - Jo-Anne Manski-Nankervis
- Department of General Practice and Primary Care, The University of Melbourne, Melbourne, Australia
| | - Ian Williams
- Department of General Practice and Primary Care, The University of Melbourne, Melbourne, Australia
| | - Barbara Hunter
- Department of General Practice and Primary Care, The University of Melbourne, Melbourne, Australia
| | - Craig Nelson
- Western Health Chronic Disease Alliance, Western Health Melbourne, Victoria, Australia; Department of Medicine - Western Health, The University of Melbourne, Melbourne, Australia
| | - Javiera Martinez-Gutierrez
- Department of General Practice and Primary Care, The University of Melbourne, Melbourne, Australia; Centre for Cancer Research, University of Melbourne, Melbourne, Australia; Department of Family Medicine, School of Medicine. Pontificia Universidad Católica de Chile, Santiago, Chile.
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Bell SK, Dong ZJ, Desroches CM, Hart N, Liu S, Mahon B, Ngo LH, Thomas EJ, Bourgeois F. Partnering with patients and families living with chronic conditions to coproduce diagnostic safety through OurDX: a previsit online engagement tool. J Am Med Inform Assoc 2023; 30:692-702. [PMID: 36692204 PMCID: PMC10018262 DOI: 10.1093/jamia/ocad003] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/27/2022] [Accepted: 01/10/2023] [Indexed: 01/25/2023] Open
Abstract
OBJECTIVE Patients and families are key partners in diagnosis, but methods to routinely engage them in diagnostic safety are lacking. Policy mandating patient access to electronic health information presents new opportunities. We tested a new online tool ("OurDX") that was codesigned with patients and families, to determine the types and frequencies of potential safety issues identified by patients/families with chronic health conditions and whether their contributions were integrated into the visit note. METHODS Patients/families at 2 US healthcare sites were invited to contribute, through an online previsit survey: (1) visit priorities, (2) recent medical history/symptoms, and (3) potential diagnostic concerns. Two physicians reviewed patient-reported diagnostic concerns to verify and categorize diagnostic safety opportunities (DSOs). We conducted a chart review to determine whether patient contributions were integrated into the note. We used descriptive statistics to report implementation outcomes, verification of DSOs, and chart review findings. RESULTS Participants completed OurDX reports in 7075 of 18 129 (39%) eligible pediatric subspecialty visits (site 1), and 460 of 706 (65%) eligible adult primary care visits (site 2). Among patients reporting diagnostic concerns, 63% were verified as probable DSOs. In total, probable DSOs were identified by 7.5% of pediatric and adult patients/families with underlying health conditions, respectively. The most common types of DSOs were patients/families not feeling heard; problems/delays with tests or referrals; and problems/delays with explanation or next steps. In chart review, most clinician notes included all or some patient/family priorities and patient-reported histories. CONCLUSIONS OurDX can help engage patients and families living with chronic health conditions in diagnosis. Participating patients/families identified DSOs and most of their OurDX contributions were included in the visit note.
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Affiliation(s)
- Sigall K Bell
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Zhiyong J Dong
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Catherine M Desroches
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Nicholas Hart
- Department of Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Stephen Liu
- Department of Medicine, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Brianna Mahon
- Department of Medicine, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Long H Ngo
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Eric J Thomas
- Department of Medicine, UT Houston—Memorial Hermann Center for Healthcare Quality and Safety, Houston, Texas, USA
- McGovern Medical School at the University of Texas Health Science Center, Houston, Texas, USA
| | - Fabienne Bourgeois
- Department of Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
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Chima S, Martinez-Gutierrez J, Hunter B, Manski-Nankervis JA, Emery J. Optimization of a Quality Improvement Tool for Cancer Diagnosis in Primary Care: Qualitative Study. JMIR Form Res 2022; 6:e39277. [PMID: 35925656 PMCID: PMC9389376 DOI: 10.2196/39277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 07/07/2022] [Accepted: 07/07/2022] [Indexed: 11/17/2022] Open
Abstract
Background The most common route to a diagnosis of cancer is through primary care. Delays in diagnosing cancer occur when an opportunity to make a timely diagnosis is missed and is evidenced by patients visiting the general practitioner (GP) on multiple occasions before referral to a specialist. Tools that minimize prolonged diagnostic intervals and reduce missed opportunities to investigate patients for cancer are therefore a priority. Objective This study aims to explore the usefulness and feasibility of a novel quality improvement (QI) tool in which algorithms flag abnormal test results that may be indicative of undiagnosed cancer. This study allows for the optimization of the cancer recommendations before testing the efficacy in a randomized controlled trial. Methods GPs, practice nurses, practice managers, and consumers were recruited to participate in individual interviews or focus groups. Participants were purposively sampled as part of a pilot and feasibility study, in which primary care practices were receiving recommendations relating to the follow-up of abnormal test results for prostate-specific antigen, thrombocytosis, and iron-deficiency anemia. The Clinical Performance Feedback Intervention Theory (CP-FIT) was applied to the analysis using a thematic approach. Results A total of 17 interviews and 3 focus groups (n=18) were completed. Participant themes were mapped to CP-FIT across the constructs of context, recipient, and feedback variables. The key facilitators to use were alignment with workflow, recognized need, the perceived importance of the clinical topic, and the GPs’ perception that the recommendations were within their control. Barriers to use included competing priorities, usability and complexity of the recommendations, and knowledge of the clinical topic. There was consistency between consumer and practitioner perspectives, reporting language concerns associated with the word cancer, the need for more patient-facing resources, and time constraints of the consultation to address patients’ worries. Conclusions There was a recognized need for the QI tool to support the diagnosis of cancer in primary care, but barriers were identified that hindered the usability and actionability of the recommendations in practice. In response, the tool has been refined and is currently being evaluated as part of a randomized controlled trial. Successful and effective implementation of this QI tool could support the detection of patients at risk of undiagnosed cancer in primary care and assist in preventing unnecessary delays.
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Affiliation(s)
- Sophie Chima
- Centre for Cancer Research, Victorian Comprehensive Cancer Centre, University of Melbourne, Melbourne, Australia
- Department of General Practice, University of Melbourne, Melbourne, Australia
| | - Javiera Martinez-Gutierrez
- Centre for Cancer Research, Victorian Comprehensive Cancer Centre, University of Melbourne, Melbourne, Australia
- Department of General Practice, University of Melbourne, Melbourne, Australia
- Department of Family Medicine, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Barbara Hunter
- Department of General Practice, University of Melbourne, Melbourne, Australia
| | | | - Jon Emery
- Centre for Cancer Research, Victorian Comprehensive Cancer Centre, University of Melbourne, Melbourne, Australia
- Department of General Practice, University of Melbourne, Melbourne, Australia
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Decision support tools to improve cancer diagnostic decision making in primary care: a systematic review. Br J Gen Pract 2019; 69:e809-e818. [PMID: 31740460 DOI: 10.3399/bjgp19x706745] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 08/26/2019] [Indexed: 10/31/2022] Open
Abstract
BACKGROUND The diagnosis of cancer in primary care is complex and challenging. Electronic clinical decision support tools (eCDSTs) have been proposed as an approach to improve GP decision making, but no systematic review has examined their role in cancer diagnosis. AIM To investigate whether eCDSTs improve diagnostic decision making for cancer in primary care and to determine which elements influence successful implementation. DESIGN AND SETTING A systematic review of relevant studies conducted worldwide and published in English between 1 January 1998 and 31 December 2018. METHOD Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were searched, and a consultation of reference lists and citation tracking was carried out. Exclusion criteria included the absence of eCDSTs used in asymptomatic populations, and studies that did not involve support delivered to the GP. The most relevant Joanna Briggs Institute Critical Appraisal Checklists were applied according to study design of the included paper. RESULTS Of the nine studies included, three showed improvements in decision making for cancer diagnosis, three demonstrated positive effects on secondary clinical or health service outcomes such as prescribing, quality of referrals, or cost-effectiveness, and one study found a reduction in time to cancer diagnosis. Barriers to implementation included trust, the compatibility of eCDST recommendations with the GP's role as a gatekeeper, and impact on workflow. CONCLUSION eCDSTs have the capacity to improve decision making for a cancer diagnosis, but the optimal mode of delivery remains unclear. Although such tools could assist GPs in the future, further well-designed trials of all eCDSTs are needed to determine their cost-effectiveness and the most appropriate implementation methods.
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Abimanyi-Ochom J, Bohingamu Mudiyanselage S, Catchpool M, Firipis M, Wanni Arachchige Dona S, Watts JJ. Strategies to reduce diagnostic errors: a systematic review. BMC Med Inform Decis Mak 2019; 19:174. [PMID: 31470839 PMCID: PMC6716834 DOI: 10.1186/s12911-019-0901-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 08/22/2019] [Indexed: 12/18/2022] Open
Abstract
Background To evaluate the effectiveness of audit and communication strategies to reduce diagnostic errors made by clinicians. Methods MEDLINE complete, CINHAL complete, EMBASE, PSNet and Google Advanced. Electronic and manual search of articles on audit systems and communication strategies or interventions, searched for papers published between January 1990 and April 2017. We included studies with interventions implemented by clinicians in a clinical environment with real patients. Results A total of 2431 articles were screened of which 26 studies met inclusion criteria. Data extraction was conducted by two groups, each group comprising two independent reviewers. Articles were classified by communication (6) or audit strategies (20) to reduce diagnostic error in clinical settings. The most common interventions were delivered as technology-based systems n = 16 (62%) and within an acute care setting n = 15 (57%). Nine studies reported randomised controlled trials. Three RCT studies on communication interventions and 3 RCTs on audit strategies found the interventions to be effective in reducing diagnostic errors. Conclusion Despite numerous studies on interventions targeting diagnostic errors, our analyses revealed limited evidence on interventions being practically used in clinical settings and a bias of studies originating from the US (n = 19, 73% of included studies). There is some evidence that trigger algorithms, including computer based and alert systems, may reduce delayed diagnosis and improve diagnostic accuracy. In trauma settings, strategies such as additional patient review (e.g. trauma teams) reduced missed diagnosis and in radiology departments review strategies such as team meetings and error documentation may reduce diagnostic error rates over time. Trial registration The systematic review was registered in the PROSPERO database under registration number CRD42017067056. Electronic supplementary material The online version of this article (10.1186/s12911-019-0901-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Julie Abimanyi-Ochom
- Deakin Health Economics, Centre for Population Health Research, Deakin University, Locked Bag 20000, Geelong, Victoria, 3220, Australia
| | - Shalika Bohingamu Mudiyanselage
- Deakin Health Economics, Centre for Population Health Research, Deakin University, Locked Bag 20000, Geelong, Victoria, 3220, Australia
| | - Max Catchpool
- Deakin Health Economics, Centre for Population Health Research, Deakin University, Locked Bag 20000, Geelong, Victoria, 3220, Australia.,Centre for Health Policy, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie St, Carlton, VIC, 3053, Australia
| | - Marnie Firipis
- Deakin Health Economics, Centre for Population Health Research, Deakin University, Locked Bag 20000, Geelong, Victoria, 3220, Australia
| | - Sithara Wanni Arachchige Dona
- Deakin Health Economics, Centre for Population Health Research, Deakin University, Locked Bag 20000, Geelong, Victoria, 3220, Australia
| | - Jennifer J Watts
- Deakin Health Economics, Centre for Population Health Research, Deakin University, Locked Bag 20000, Geelong, Victoria, 3220, Australia.
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Emani S, Sequist TD, Lacson R, Khorasani R, Jajoo K, Holtz L, Desai S. Ambulatory Safety Nets to Reduce Missed and Delayed Diagnoses of Cancer. Jt Comm J Qual Patient Saf 2019; 45:552-557. [PMID: 31285149 PMCID: PMC7545363 DOI: 10.1016/j.jcjq.2019.05.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2019] [Revised: 05/23/2019] [Accepted: 05/29/2019] [Indexed: 12/02/2022]
Abstract
BACKGROUND An ambulatory safety net (ASN) is an innovative organizational intervention for addressing patient safety related to missed and delayed diagnoses of abnormal test results. ASNs consist of a set of tools, reports and registries, and associated work flows to create a high-reliability system for abnormal test result management. METHODS Two ASNs implemented at an academic medical center are described, one focusing on colon cancer and the other on lung cancer. Data from electronic registries and chart reviews were used to evaluate the effectiveness of the ASNs, which were defined as follows: colon cancer-the proportion of patients who were scheduled for or completed a colonoscopy following safety net team outreach to the patient; lung cancer-the proportion of patients for whom the safety net was able to identify and implement appropriate follow-up, as defined by scheduled or completed chest CT. RESULTS The effectiveness of the colon cancer ASN was 44.0%, and the effectiveness of the lung cancer ASN was 56.9%. The ASNs led to the development of registries to address patient safety, fostered collaboration among interdisciplinary teams of clinicians and administrative staff, and created new work flows for patient outreach and tracking. CONCLUSION Two ASNs were successfully implemented at an academic medical center to address missed and delayed recognition of abnormal test results related to colon cancer and lung cancer. The ASNs are providing a framework for development of additional safety nets in the organization.
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Murphy DR, Meyer AN, Sittig DF, Meeks DW, Thomas EJ, Singh H. Application of electronic trigger tools to identify targets for improving diagnostic safety. BMJ Qual Saf 2019; 28:151-159. [PMID: 30291180 PMCID: PMC6365920 DOI: 10.1136/bmjqs-2018-008086] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Revised: 06/20/2018] [Accepted: 08/14/2018] [Indexed: 02/05/2023]
Abstract
Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals indicative of a likely error or adverse event, offer a promising method to efficiently identify errors. The increasing amounts of longitudinal electronic data and maturing data warehousing techniques and infrastructure offer an unprecedented opportunity to implement new types of e-trigger tools that use algorithms to identify risks and events related to the diagnostic process. We present a knowledge discovery framework, the Safer Dx Trigger Tools Framework, that enables health systems to develop and implement e-trigger tools to identify and measure diagnostic errors using comprehensive electronic health record (EHR) data. Safer Dx e-trigger tools detect potential diagnostic events, allowing health systems to monitor event rates, study contributory factors and identify targets for improving diagnostic safety. In addition to promoting organisational learning, some e-triggers can monitor data prospectively and help identify patients at high-risk for a future adverse event, enabling clinicians, patients or safety personnel to take preventive actions proactively. Successful application of electronic algorithms requires health systems to invest in clinical informaticists, information technology professionals, patient safety professionals and clinicians, all of who work closely together to overcome development and implementation challenges. We outline key future research, including advances in natural language processing and machine learning, needed to improve effectiveness of e-triggers. Integrating diagnostic safety e-triggers in institutional patient safety strategies can accelerate progress in reducing preventable harm from diagnostic errors.
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Affiliation(s)
- Daniel R Murphy
- Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Ashley Nd Meyer
- Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Dean F Sittig
- Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
- School of Biomedical Informatics, University of Texas Health Science Center, Houston, Texas, USA
- Department of Medicine, University of Texas-Memorial Hermann Center for Healthcare Quality and Safety, Houston, Texas, USA
| | - Derek W Meeks
- Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Eric J Thomas
- Department of Medicine, University of Texas-Memorial Hermann Center for Healthcare Quality and Safety, Houston, Texas, USA
| | - Hardeep Singh
- Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
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Percac-Lima S, Pace LE, Nguyen KH, Crofton CN, Normandin KA, Singer SJ, Rosenthal MB, Chien AT. Diagnostic Evaluation of Patients Presenting to Primary Care with Rectal Bleeding. J Gen Intern Med 2018; 33:415-422. [PMID: 29302885 PMCID: PMC5880768 DOI: 10.1007/s11606-017-4273-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Revised: 10/31/2017] [Accepted: 12/05/2017] [Indexed: 12/25/2022]
Abstract
BACKGROUND Rectal bleeding is a common, frequently benign problem that can also be an early sign of colorectal cancer. Diagnostic evaluation for rectal bleeding is complex, and clinical practice may deviate from available guidelines. OBJECTIVE To assess the degree to which primary care physicians document risk factors for colorectal cancer among patients with rectal bleeding and order colonoscopies when indicated, and the likelihood of physicians ordering and patients receiving recommended colonoscopies based on demographic characteristics, visit patterns, and clinical presentations. DESIGN Cross-sectional study using explicit chart abstraction methods. PARTICIPANTS Three hundred adults, 40-80 years of age, presenting with rectal bleeding to 15 academically affiliated primary care practices between 2012 and 2016. MAIN MEASURES 1) The frequency at which colorectal cancer risk factors were documented in patients' charts, 2) the frequency at which physicians ordered colonoscopies and patients received them, and 3) the odds of ordering and patients receiving recommended colonoscopies based on patient demographic characteristics, visit patterns, and clinical presentations. KEY RESULTS Risk factors for colorectal cancer were documented between 9% and 66% of the time. Most patients (89%) with rectal bleeding needed a colonoscopy according to a clinical guideline. Physicians placed colonoscopy orders for 74% of these patients, and 56% completed the colonoscopy within a year (36% within 60 days). The odds of physicians ordering recommended colonoscopies were significantly higher in patients aged 50-64 years of age than in those aged 40-50 years (OR = 2.23, 95% CI: 1.04, 4.80), and for patients whose most recent colonoscopy was 5 or more years ago (OR = 4.04, 95% CI: 1.50, 10.83). The odds of physicians ordering and patients receiving recommended colonoscopies were significantly lower for each primary care visit unrelated to rectal bleeding (OR = 0.85, 95% CI: 0.75, 0.96). CONCLUSIONS Diagnostic evaluation of patients presenting to primary care with rectal bleeding may be suboptimal because of inadequate risk factor assessment and prioritization of patients' other concurrent medical problems.
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Affiliation(s)
- Sanja Percac-Lima
- Harvard Medical School, Boston, MA, USA.
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
| | - Lydia E Pace
- Harvard Medical School, Boston, MA, USA
- Division of Women's Health, Brigham and Women's Hospital, Boston, MA, USA
| | - Kevin H Nguyen
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Charis N Crofton
- Division of General Pediatrics, Department of Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Katharine A Normandin
- Division of General Pediatrics, Department of Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Sara J Singer
- Harvard Medical School, Boston, MA, USA
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Mongan Institute, Massachusetts General Hospital, Boston, MA, USA
| | - Meredith B Rosenthal
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Alyna T Chien
- Harvard Medical School, Boston, MA, USA
- Division of General Pediatrics, Department of Medicine, Boston Children's Hospital, Boston, MA, USA
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Meyer AND, Murphy DR, Al-Mutairi A, Sittig DF, Wei L, Russo E, Singh H. Electronic Detection of Delayed Test Result Follow-Up in Patients with Hypothyroidism. J Gen Intern Med 2017; 32:753-759. [PMID: 28138875 PMCID: PMC5481223 DOI: 10.1007/s11606-017-3988-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 12/20/2016] [Accepted: 01/05/2017] [Indexed: 02/05/2023]
Abstract
BACKGROUND Delays in following up abnormal test results are a common problem in outpatient settings. Surveillance systems that use trigger tools to identify delayed follow-up can help reduce missed opportunities in care. OBJECTIVE To develop and test an electronic health record (EHR)-based trigger algorithm to identify instances of delayed follow-up of abnormal thyroid-stimulating hormone (TSH) results in patients being treated for hypothyroidism. DESIGN We developed an algorithm using structured EHR data to identify patients with hypothyroidism who had delayed follow-up (>60 days) after an abnormal TSH. We then retrospectively applied the algorithm to a large EHR data warehouse within the Department of Veterans Affairs (VA), on patient records from two large VA networks for the period from January 1, 2011, to December 31, 2011. Identified records were reviewed to confirm the presence of delays in follow-up. KEY RESULTS During the study period, 645,555 patients were seen in the outpatient setting within the two networks. Of 293,554 patients with at least one TSH test result, the trigger identified 1250 patients on treatment for hypothyroidism with elevated TSH. Of these patients, 271 were flagged as potentially having delayed follow-up of their test result. Chart reviews confirmed delays in 163 of the 271 flagged patients (PPV = 60.1%). CONCLUSIONS An automated trigger algorithm applied to records in a large EHR data warehouse identified patients with hypothyroidism with potential delays in thyroid function test results follow-up. Future prospective application of the TSH trigger algorithm can be used by clinical teams as a surveillance and quality improvement technique to monitor and improve follow-up.
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Affiliation(s)
- Ashley N D Meyer
- Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center and Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
| | - Daniel R Murphy
- Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center and Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Aymer Al-Mutairi
- Department of Family & Community Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Dean F Sittig
- School of Biomedical Informatics and UT-Memorial Hermann Center for Healthcare Quality and Safety, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Li Wei
- Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center and Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Elise Russo
- Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center and Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Hardeep Singh
- Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center and Department of Medicine, Baylor College of Medicine, Houston, TX, USA
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