Skip to main content
Top
Published in: Implementation Science 1/2017

Open Access 01-12-2017 | Research

Implementation science for ambulatory care safety: a novel method to develop context-sensitive interventions to reduce quality gaps in monitoring high-risk patients

Authors: Kathryn M. McDonald, George Su, Sarah Lisker, Emily S. Patterson, Urmimala Sarkar

Published in: Implementation Science | Issue 1/2017

Login to get access

Abstract

Background

Missed evidence-based monitoring in high-risk conditions (e.g., cancer) leads to delayed diagnosis. Current technological solutions fail to close this safety gap. In response, we aim to demonstrate a novel method to identify common vulnerabilities across clinics and generate attributes for context-flexible population-level monitoring solutions for widespread implementation to improve quality.

Methods

Based on interviews with staff in otolaryngology, pulmonary, urology, breast, and gastroenterology clinics at a large urban publicly funded health system, we applied journey mapping to co-develop a visual representation of how patients are monitored for high-risk conditions. Using a National Academies framework and context-sensitivity theory, we identified common systems vulnerabilities and developed preliminary concepts for improving the robustness for monitoring patients with high-risk conditions (“design seeds” for potential solutions). Finally, we conducted a face validity and prioritization assessment of the design seeds with the original interviewees.

Results

We identified five high-risk situations for potentially consequential diagnostic delays arising from suboptimal patient monitoring. All situations related to detection of cancer (head and neck, lung, prostate, breast, and colorectal). With clinic participants we created 5 journey maps, each representing specialty clinic workflow directed at evidence-based monitoring. System vulnerabilities common to the different clinics included challenges with: data systems, communications handoffs, population-level tracking, and patient activities. Clinic staff ranked 13 design seeds (e.g., keep patient list up to date, use triggered notifications) addressing these vulnerabilities. Each design seed has unique evaluation criteria for the usefulness of potential solutions developed from the seed.

Conclusions

We identified and ranked 13 design seeds that characterize situations that clinicians described ‘wake them up at night’, and thus could reduce their anxiety, save time, and improve monitoring of high-risk patients. We anticipate that the design seed approach promotes robust and context-sensitive solutions to safety and quality problems because it provides a human-centered link between the experienced problem and various solutions that can be tested for viability. The study also demonstrates a novel integration of industrial and human factors methods (journey mapping, process tracing and design seeds) linked to implementation theory for use in designing interventions that anticipate and reduce implementation challenges.
Appendix
Available only for authorised users
Footnotes
1
Patient monitoring for cancer, in this paper, is broadly construed to include an expansive set of diagnostic opportunities, not just one definitive and staged cancer diagnosis. Ambulatory safety risk in this context includes identification of high-risk patients, pre-diagnosis testing, definitive diagnostic procedures (e.g., biopsies), and even longitudinal post-diagnosis follow up (e.g., keeping track of patients for whom treatment is delayed on purpose, or following patients after treatment for cancer recurrence).
 
Literature
4.
go back to reference Hoffman J, editor. Annual Benchmarking Report: Malpractice Risks in the Diagnostic Process. Cambridge: CRICO Strategies; 2014;1–20. Hoffman J, editor. Annual Benchmarking Report: Malpractice Risks in the Diagnostic Process. Cambridge: CRICO Strategies; 2014;1–20.
6.
go back to reference Schiff GD, Hasan O, Kim S, Abrams R, Cosby K, Lambert BL, et al. Diagnostic error in medicine: analysis of 583 physician-reported errors. Arch Intern Med. 2009;169:1881–7.CrossRefPubMed Schiff GD, Hasan O, Kim S, Abrams R, Cosby K, Lambert BL, et al. Diagnostic error in medicine: analysis of 583 physician-reported errors. Arch Intern Med. 2009;169:1881–7.CrossRefPubMed
9.
go back to reference Mohler JL, Armstrong AJ, Bahnson RR, D’Amico A, Davis BJ, Eastham JA, et al. NCCN Clinical Practice Guidelines in Oncology - Prostate Cancer. 2016. Mohler JL, Armstrong AJ, Bahnson RR, D’Amico A, Davis BJ, Eastham JA, et al. NCCN Clinical Practice Guidelines in Oncology - Prostate Cancer. 2016.
12.
go back to reference Wood DE, Kazerooni EA, Baum SL, Eapen GA, Ettinger DS, Hou L, et al. National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines for Lung Cancer Screening. Thorac Surg Clin. 2015;25:185–97.CrossRefPubMed Wood DE, Kazerooni EA, Baum SL, Eapen GA, Ettinger DS, Hou L, et al. National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines for Lung Cancer Screening. Thorac Surg Clin. 2015;25:185–97.CrossRefPubMed
15.
go back to reference Carroll PR, Parsons JK, Andriole G, Bahnson RR, Castle EP, Catalona WJ, et al. Prostate cancer early detection, Version 2.2016: Featured updates to the NCCN guidelines. JNCCN J Natl Comprehensive Cancer Netw. 2016;14:509–19.CrossRef Carroll PR, Parsons JK, Andriole G, Bahnson RR, Castle EP, Catalona WJ, et al. Prostate cancer early detection, Version 2.2016: Featured updates to the NCCN guidelines. JNCCN J Natl Comprehensive Cancer Netw. 2016;14:509–19.CrossRef
19.
go back to reference Haas JS, Cook EF, Puopolo AL, Burstin HR, Brennan TA. Differences in the quality of care for women with an abnormal mammogram or breast complaint. J Gen Intern Med. 2000;15:321–8.CrossRefPubMedPubMedCentral Haas JS, Cook EF, Puopolo AL, Burstin HR, Brennan TA. Differences in the quality of care for women with an abnormal mammogram or breast complaint. J Gen Intern Med. 2000;15:321–8.CrossRefPubMedPubMedCentral
20.
go back to reference Chang SW, Kerlikowske K, Napoles-Springer A, Posner SF, Sickles EA, Perez-Stable EJ. Racial differences in timeliness of follow-up after abnormal screening mammography. Cancer. 1996;78:1395–402.CrossRefPubMed Chang SW, Kerlikowske K, Napoles-Springer A, Posner SF, Sickles EA, Perez-Stable EJ. Racial differences in timeliness of follow-up after abnormal screening mammography. Cancer. 1996;78:1395–402.CrossRefPubMed
23.
go back to reference Blagev DP, Lloyd JF, Conner K, Dickerson J, Adams D, Stevens SM, et al. Follow-up of Incidental Pulmonary Nodules and the Radiology Report. J Am Coll Radiol. 2016;13:R18–24.CrossRefPubMed Blagev DP, Lloyd JF, Conner K, Dickerson J, Adams D, Stevens SM, et al. Follow-up of Incidental Pulmonary Nodules and the Radiology Report. J Am Coll Radiol. 2016;13:R18–24.CrossRefPubMed
24.
go back to reference Goldman LE, Walker R, Hubbard R, Kerlikowske K. Timeliness of abnormal screening and diagnostic mammography follow-up at facilities serving vulnerable women. Med Care. 2013;51:307–14.CrossRefPubMedPubMedCentral Goldman LE, Walker R, Hubbard R, Kerlikowske K. Timeliness of abnormal screening and diagnostic mammography follow-up at facilities serving vulnerable women. Med Care. 2013;51:307–14.CrossRefPubMedPubMedCentral
25.
go back to reference Martin J, Halm EA, Tiro JA, Merchant Z, Balasubramanian BA, McCallister K, et al. Reasons for Lack of Diagnostic Colonoscopy After Positive Result on Fecal Immunochemical Test in a Safety-Net Health System. Am J Med. 2016;130:93.e1-93.e7 Martin J, Halm EA, Tiro JA, Merchant Z, Balasubramanian BA, McCallister K, et al. Reasons for Lack of Diagnostic Colonoscopy After Positive Result on Fecal Immunochemical Test in a Safety-Net Health System. Am J Med. 2016;130:93.e1-93.e7
26.
go back to reference Oluloro A, Petrik AF, Turner A, Kapka T, Rivelli J, Carney PA, et al. Timeliness of Colonoscopy After Abnormal Fecal Test Results in a Safety Net Practice. J Community Health. 2016;41:864–70.CrossRefPubMed Oluloro A, Petrik AF, Turner A, Kapka T, Rivelli J, Carney PA, et al. Timeliness of Colonoscopy After Abnormal Fecal Test Results in a Safety Net Practice. J Community Health. 2016;41:864–70.CrossRefPubMed
27.
go back to reference Issaka RB, Singh MH, Oshima SM, Laleau VJ, Rachocki CD, Chen EH, et al. Inadequate Utilization of Diagnostic Colonoscopy Following Abnormal FIT Results in an Integrated Safety-Net System. Am J Gastroenterol. 2017;112:375-82. doi: 10.1038/ajg.2016.555. Issaka RB, Singh MH, Oshima SM, Laleau VJ, Rachocki CD, Chen EH, et al. Inadequate Utilization of Diagnostic Colonoscopy Following Abnormal FIT Results in an Integrated Safety-Net System. Am J Gastroenterol. 2017;112:375-82. doi: 10.​1038/​ajg.​2016.​555.
28.
go back to reference Bickell NA, Moss AD, Castaldi M, Shah A, Sickles A, Pappas P, et al. Organizational Factors Affect Safety-Net Hospitals’ Breast Cancer Treatment Rates. Health Serv Res. 2016. [Epub ahead of print]. Bickell NA, Moss AD, Castaldi M, Shah A, Sickles A, Pappas P, et al. Organizational Factors Affect Safety-Net Hospitals’ Breast Cancer Treatment Rates. Health Serv Res. 2016. [Epub ahead of print].
30.
go back to reference Ash JS, Berg M, Coiera E. Some unintended consequences of information technology in health care: the nature of patient care information system-related errors. J Am Med Inf Assoc. 2004;11:104–12.CrossRef Ash JS, Berg M, Coiera E. Some unintended consequences of information technology in health care: the nature of patient care information system-related errors. J Am Med Inf Assoc. 2004;11:104–12.CrossRef
31.
go back to reference Moore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ. 2015;350:h1258.CrossRefPubMedPubMedCentral Moore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ. 2015;350:h1258.CrossRefPubMedPubMedCentral
32.
go back to reference Kent EE, Mitchell SA, Castro KM, DeWalt DA, Kaluzny AD, Hautala JA, et al. Cancer Care Delivery Research: Building the Evidence Base to Support Practice Change in Community Oncology. J Clin Oncol. 2015;33:2705–11.CrossRefPubMedPubMedCentral Kent EE, Mitchell SA, Castro KM, DeWalt DA, Kaluzny AD, Hautala JA, et al. Cancer Care Delivery Research: Building the Evidence Base to Support Practice Change in Community Oncology. J Clin Oncol. 2015;33:2705–11.CrossRefPubMedPubMedCentral
34.
go back to reference Carayon P, Hundt AS, Karsh B-T, Gurses AP, Alvarado CJ, Smith M, et al. Work system design for patient safety: the SEIPS model. Qual Saf Heal Care. 2006;15 Suppl I:i50–8.CrossRef Carayon P, Hundt AS, Karsh B-T, Gurses AP, Alvarado CJ, Smith M, et al. Work system design for patient safety: the SEIPS model. Qual Saf Heal Care. 2006;15 Suppl I:i50–8.CrossRef
35.
go back to reference Carayon P, Wetterneck TB, Rivera-Rodriguez AJ, Hundt AS, Hoonakker P, Holden R, et al. Human factors systems approach to healthcare quality and patient safety. Appl Erg. 2014;45:14–25.CrossRef Carayon P, Wetterneck TB, Rivera-Rodriguez AJ, Hundt AS, Hoonakker P, Holden R, et al. Human factors systems approach to healthcare quality and patient safety. Appl Erg. 2014;45:14–25.CrossRef
38.
go back to reference Bruce BB, El-Kareh R, Ely JW, Kanter MH, Rao G, Schiff GD, et al. Methodologies for evaluating strategies to reduce diagnostic error: report from the research summit at the 7th International Diagnostic Error in Medicine Conference. Diagnosis. 2016;3:1–7.CrossRef Bruce BB, El-Kareh R, Ely JW, Kanter MH, Rao G, Schiff GD, et al. Methodologies for evaluating strategies to reduce diagnostic error: report from the research summit at the 7th International Diagnostic Error in Medicine Conference. Diagnosis. 2016;3:1–7.CrossRef
39.
go back to reference Taylor SL, Dy S, Foy R, Hempel S, McDonald KM, Ovretveit J, et al. What context features might be important determinants of the effectiveness of patient safety practice interventions? BMJ Qual Saf. 2011;20:611–7.CrossRefPubMed Taylor SL, Dy S, Foy R, Hempel S, McDonald KM, Ovretveit J, et al. What context features might be important determinants of the effectiveness of patient safety practice interventions? BMJ Qual Saf. 2011;20:611–7.CrossRefPubMed
43.
go back to reference Boyd H, McKernon S, Mullin B, Old A. Improving healthcare through the use of co-design. N Z Med J. 2012;125:76–87.PubMed Boyd H, McKernon S, Mullin B, Old A. Improving healthcare through the use of co-design. N Z Med J. 2012;125:76–87.PubMed
45.
go back to reference Militello LG, Patterson ES, Saleem J, Anders S, Asch S. Supporting Macrocognition in Health Care: Improving Clinical Reminders. In: Schraagen JM, Ormerod T, Lipshitz R, Militello LG, editors. Naturalistic Decision Making and Macrocognition. Hampshire: Ashgate; 2008. p. 203–20. Militello LG, Patterson ES, Saleem J, Anders S, Asch S. Supporting Macrocognition in Health Care: Improving Clinical Reminders. In: Schraagen JM, Ormerod T, Lipshitz R, Militello LG, editors. Naturalistic Decision Making and Macrocognition. Hampshire: Ashgate; 2008. p. 203–20.
46.
go back to reference Patterson ES, Rogers ML, Tomolo AM, Wears RL, Tsevat J. Comparison of extent of use, information accuracy, and functions for manual and electronic patient status boards. Int J Med Inform. 2010;79:817–23. doi: 10.1016/j.ijmedinf.2010.08.002. Patterson ES, Rogers ML, Tomolo AM, Wears RL, Tsevat J. Comparison of extent of use, information accuracy, and functions for manual and electronic patient status boards. Int J Med Inform. 2010;79:817–23. doi: 10.​1016/​j.​ijmedinf.​2010.​08.​002.
47.
go back to reference Patterson ES, Woods DD, Roth EM. Using Cognitive Task Analysis (CTA) to Seed Design Concepts for Intelligence Analysts Under Data Overload. Hum Factors Ergon Soc Annu Meet Proc. 2001;45. doi:10.1177/154193120104500437. Patterson ES, Woods DD, Roth EM. Using Cognitive Task Analysis (CTA) to Seed Design Concepts for Intelligence Analysts Under Data Overload. Hum Factors Ergon Soc Annu Meet Proc. 2001;45. doi:10.​1177/​1541931201045004​37.
49.
go back to reference Sittig DF, Singh H. A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. Qual Saf Heal Care. 2010;19 Suppl 3:i68–74.CrossRef Sittig DF, Singh H. A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. Qual Saf Heal Care. 2010;19 Suppl 3:i68–74.CrossRef
53.
54.
go back to reference Vest JR, Gamm LD. A critical review of the research literature on Six Sigma, Lean and StuderGroup’s Hardwiring Excellence in the United States: the need to demonstrate and communicate the effectiveness of transformation strategies in healthcare. Implement Sci. 2009;4:35. doi:10.1186/1748-5908-4–35. Vest JR, Gamm LD. A critical review of the research literature on Six Sigma, Lean and StuderGroup’s Hardwiring Excellence in the United States: the need to demonstrate and communicate the effectiveness of transformation strategies in healthcare. Implement Sci. 2009;4:35. doi:10.​1186/​1748-5908-4–35.
55.
go back to reference Saber Tehrani AS, Lee H, Mathews SC, Shore A, Makary MA, Pronovost PJ, et al. 25-Year summary of US malpractice claims for diagnostic errors 1986–2010: an analysis from the National Practitioner Data Bank. BMJ Qual Saf. 2013;22:672–80. doi:10.1136/bmjqs-2012-001550.CrossRefPubMed Saber Tehrani AS, Lee H, Mathews SC, Shore A, Makary MA, Pronovost PJ, et al. 25-Year summary of US malpractice claims for diagnostic errors 1986–2010: an analysis from the National Practitioner Data Bank. BMJ Qual Saf. 2013;22:672–80. doi:10.​1136/​bmjqs-2012-001550.CrossRefPubMed
56.
go back to reference Franco J, Elghouche AN, Harris MS, Kokoska MS. Diagnostic Delays and Errors in Head and Neck Cancer Patients: Opportunities for Improvement. Am J Med Qual. 2016;32:330–35. Franco J, Elghouche AN, Harris MS, Kokoska MS. Diagnostic Delays and Errors in Head and Neck Cancer Patients: Opportunities for Improvement. Am J Med Qual. 2016;32:330–35.
57.
go back to reference Paul MM, Greene CM, Newton-Dame R, Thorpe LE, Perlman SE, McVeigh KH, et al. The state of population health surveillance using electronic health records: a narrative review. Popul Heal Manag. 2015;18:209–16.CrossRef Paul MM, Greene CM, Newton-Dame R, Thorpe LE, Perlman SE, McVeigh KH, et al. The state of population health surveillance using electronic health records: a narrative review. Popul Heal Manag. 2015;18:209–16.CrossRef
58.
go back to reference Carayon P Cartmill RS, et al KB. Incorporating Health Information Technology Into Workflow Redesign--Summary Report. Rockville: Agency for Healthcare Research and Quality; 2010. Carayon P Cartmill RS, et al KB. Incorporating Health Information Technology Into Workflow Redesign--Summary Report. Rockville: Agency for Healthcare Research and Quality; 2010.
59.
go back to reference Lowry SZ, Patterson ES, Brick D, Gurses AP, Ozok A, Simmons D, et al. Integrating Electronic Health Records into Clinical Workflow: An Application of Human Factors Modeling Methods to Ambulatory Care. NIST Interagency/Internal Rep. 2014;7988. Lowry SZ, Patterson ES, Brick D, Gurses AP, Ozok A, Simmons D, et al. Integrating Electronic Health Records into Clinical Workflow: An Application of Human Factors Modeling Methods to Ambulatory Care. NIST Interagency/Internal Rep. 2014;7988.
60.
go back to reference Sarkar U, Simchowitz B, Bonacum D, Strull W, Lopez A, Rotteau L, et al. A Qualitative Analysis of Physician Perspectives on Missed and Delayed Outpatient Diagnosis: The Focus on System-Related Factors. Jt Comm J Qual Patient Saf. 2014;40:461–70. https://doi.org/10.1016/S1553-7250(14)40059-X. Accessed 10 Aug 2016. Sarkar U, Simchowitz B, Bonacum D, Strull W, Lopez A, Rotteau L, et al. A Qualitative Analysis of Physician Perspectives on Missed and Delayed Outpatient Diagnosis: The Focus on System-Related Factors. Jt Comm J Qual Patient Saf. 2014;40:461–70. https://​doi.​org/​10.​1016/​S1553-7250(14)40059-X. Accessed 10 Aug 2016.
61.
go back to reference Woods DD. Process-tracing methods for the study of cognition outside of the experimental psychology laboratory. In: Klein GA, Calderwood R, Zsambok CE, Orasanu J, editors. Decision Making in Action: Models and Methods. Norwood: Ablex Publishing Corporation; 1993. p. 228–51. Woods DD. Process-tracing methods for the study of cognition outside of the experimental psychology laboratory. In: Klein GA, Calderwood R, Zsambok CE, Orasanu J, editors. Decision Making in Action: Models and Methods. Norwood: Ablex Publishing Corporation; 1993. p. 228–51.
63.
go back to reference Middleton B, Bloomrosen M, Dente MA, Hashmat B, Koppel R, Overhage JM, et al. Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. J Am Med Informatics Assoc. 2013;20:e2–8. doi:10.1136/amiajnl-2012-001458.CrossRef Middleton B, Bloomrosen M, Dente MA, Hashmat B, Koppel R, Overhage JM, et al. Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. J Am Med Informatics Assoc. 2013;20:e2–8. doi:10.​1136/​amiajnl-2012-001458.CrossRef
64.
go back to reference Patterson ES, Cook RI, Render ML. Improving patient safety by identifying side effects from introducing bar coding in medication administration. J Am Med Inf Assoc. 2002;9:540–53. doi: 10.1197/jamia.M1061. Patterson ES, Cook RI, Render ML. Improving patient safety by identifying side effects from introducing bar coding in medication administration. J Am Med Inf Assoc. 2002;9:540–53. doi: 10.​1197/​jamia.​M1061.
65.
go back to reference Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. Safety risks associated with the lack of integration and interfacing of hospital health information technologies: a qualitative study of hospital electronic prescribing systems in England. BMJ Qual Saf. 2016. doi:10.1136/bmjqs-2015-004925. Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. Safety risks associated with the lack of integration and interfacing of hospital health information technologies: a qualitative study of hospital electronic prescribing systems in England. BMJ Qual Saf. 2016. doi:10.​1136/​bmjqs-2015-004925.
66.
go back to reference Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. Workarounds to hospital electronic prescribing systems: a qualitative study in English hospitals. BMJ Qual Saf. 2016. doi:10.1136/bmjqs-2015-005149. Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. Workarounds to hospital electronic prescribing systems: a qualitative study in English hospitals. BMJ Qual Saf. 2016. doi:10.​1136/​bmjqs-2015-005149.
67.
go back to reference Flanagan ME, Saleem JJ, Millitello LG, Russ AL, Doebbeling BN. Paper- and computer-based workarounds to electronic health record use at three benchmark institutions. J Am Med Inf Assoc. 2013;20:e59–66.CrossRef Flanagan ME, Saleem JJ, Millitello LG, Russ AL, Doebbeling BN. Paper- and computer-based workarounds to electronic health record use at three benchmark institutions. J Am Med Inf Assoc. 2013;20:e59–66.CrossRef
68.
go back to reference Braithwaite J, Marks D, Taylor N. Harnessing implementation science to improve care quality and patient safety: a systematic review of targeted literature. Int J Qual Heal care J Int Soc Qual Heal Care. 2014;26:321–9.CrossRef Braithwaite J, Marks D, Taylor N. Harnessing implementation science to improve care quality and patient safety: a systematic review of targeted literature. Int J Qual Heal care J Int Soc Qual Heal Care. 2014;26:321–9.CrossRef
69.
go back to reference Simon HA. Administrative Behavior. A Study of Decision-Making Processes in Administrative Organization. 3rd ed. London: The Free Press, Collier Macmillan Publishers; 1976. Simon HA. Administrative Behavior. A Study of Decision-Making Processes in Administrative Organization. 3rd ed. London: The Free Press, Collier Macmillan Publishers; 1976.
70.
go back to reference Rasmussen J. Skills, Rules, and Knowledge; Signals, Signs, and Symbols, and other Distinctions in Human Performance Models. IEEE Trans Syst Man Cybern. 1983;13:257–66.CrossRef Rasmussen J. Skills, Rules, and Knowledge; Signals, Signs, and Symbols, and other Distinctions in Human Performance Models. IEEE Trans Syst Man Cybern. 1983;13:257–66.CrossRef
71.
go back to reference Murphy DR, Meyer AN, Bhise V, Russo E, Sittig DF, Wei L, et al. Computerized Triggers of Big Data to Detect Delays in Follow-up of Chest Imaging Results. Chest. 2016;150:613–20. Murphy DR, Meyer AN, Bhise V, Russo E, Sittig DF, Wei L, et al. Computerized Triggers of Big Data to Detect Delays in Follow-up of Chest Imaging Results. Chest. 2016;150:613–20.
73.
go back to reference Murphy DR, Thomas EJ, Meyer AN, Singh H. Development and Validation of Electronic Health Record-based Triggers to Detect Delays in Follow-up of Abnormal Lung Imaging Findings. Radiology. 2015;277:81–7.CrossRefPubMedPubMedCentral Murphy DR, Thomas EJ, Meyer AN, Singh H. Development and Validation of Electronic Health Record-based Triggers to Detect Delays in Follow-up of Abnormal Lung Imaging Findings. Radiology. 2015;277:81–7.CrossRefPubMedPubMedCentral
74.
go back to reference Chaudoir SR, Dugan AG, Barr CHI. Measuring factors affecting implementation of health innovations: a systematic review of structural, organizational, provider, patient, and innovation level measures. Implement Sci. 2013;8:1–20. doi:10.1186/1748-5908-8-22.CrossRef Chaudoir SR, Dugan AG, Barr CHI. Measuring factors affecting implementation of health innovations: a systematic review of structural, organizational, provider, patient, and innovation level measures. Implement Sci. 2013;8:1–20. doi:10.​1186/​1748-5908-8-22.CrossRef
Metadata
Title
Implementation science for ambulatory care safety: a novel method to develop context-sensitive interventions to reduce quality gaps in monitoring high-risk patients
Authors
Kathryn M. McDonald
George Su
Sarah Lisker
Emily S. Patterson
Urmimala Sarkar
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Implementation Science / Issue 1/2017
Electronic ISSN: 1748-5908
DOI
https://doi.org/10.1186/s13012-017-0609-5

Other articles of this Issue 1/2017

Implementation Science 1/2017 Go to the issue