Optional Readings:
Session Title: Moving from Quality to Value in your Improvement Work
King, B. & Patel, R. M. Using Quality Improvement to Improve Value and Reduce Waste. Clin Perinatol (2023) doi:10.1016/j.clp.2023.01.009.
Chua, K.-P., Conti, R. M. & Freed, G. L. Appropriately Framing Child Health Care Spending: A Prerequisite for Value Improvement. JAMA 319, 1087–1088 (2018).
Liang, D., House, S. A. & Moriates, C. Improving healthcare value: The need to explicitly address equity in high‐value care. J. Hosp. Med. (2024) doi:10.1002/jhm.13280.
Tchou, M. J. et al. Reducing Electrolyte Testing in Hospitalized Children by Using Quality Improvement Methods. Pediatrics 141, (2018).
Moriates, C. & Valencia, V. Emerging principles for health system value improvement programmes. BMJ Quality & Safety bmjqs-2019-009427 (2019) doi:10.1136/bmjqs-2019-009427.
Synhorst, D. C., Gay, J. C., Harding, J. P. & Hall, M. Methods progress note: Hospital finances for the hospitalist. J Hosp Med (2023) doi:10.1002/jhm.13041.
Session Title: Pathways Reimagined: Harnessing Implementation Science, Clinical Decision Support, Artificial Intelligence, and Behavioral Nudges for Smarter Clinical Impact
Inpatient Clinical Pathway-Asthma: https://agile.md/a/3zwxTmHnkEGA411E5rFR7bP1oZY9z44aqDfrdyJhmyTCXhcgxc
Rotter T, Kinsman LD, Alsius A, Scott SD, Lawal A, Ronellenfitsch U, Plishka C, Groot G, Woods P, Coulson C, Bakel LA, Sears K, Ross-White A, Machotta A, Schultz TJ. Clinical pathways for secondary care and the effects on professional practice, patient outcomes, length of stay and hospital costs. Cochrane Database of Systematic Reviews 2025, Issue 5. Art. No.: CD006632. DOI: 10.1002/14651858.CD006632.pub3. Accessed 27 March 2026. https://doi-org.cuanschutz.idm.oclc.org/10.1002/14651858.CD006632.pub3
Tyler A, Pérez Jolles M. Methodological progress note: Implementation science contributions to healthcare research and practice. J Hosp Med. 2023; 18: 920-925. doi:10.1002/jhm.13147
Tyler, A., Glasgow, R. Implementing Improvements: Opportunities to Integrate Quality Improvement and Implementation Science. Hosp Pediatr May 2021; 11 (5): 536–545.
General regulatory, guidance and responsible use of AI
Palmieri S, Robertson CT, Cohen IG. New guidance on responsible use of AI. JAMA. 2026;335(3):207-208. doi:10.1001/jama.2025.23059
Sahni NR, Carrus B. Artificial intelligence in U.S. health care delivery. N Engl J Med. 2023;389(4):348-358. doi:10.1056/NEJMra2204673
Warraich HJ, Tazbaz T, Califf RM. FDA perspective on the regulation of artificial intelligence in health care and biomedicine. JAMA. 2025;333(3):241-247. Doi:10.1001/jama.2024.21451
Welch ML, Grant B, Deutschman C, McElcheran C, Badzynski A, Bell JAH, Hope A, Grant RC, Truong T, Lane K, Leake P, Sharma D, Stedman I, Lovas M, Petch J, Berlin A, Haibe-Kains B, Anderson JA. A practical framework for operationalising responsible and equitable artificial intelligence in health care: tackling bias, inequity, and implementation challenges. Lancet Digit Health. 2026 Mar 20:100957. doi: 10.1016/j.landig.2025.100957. Epub ahead of print. PMID: 41864789.
AI – implementation, monitoring, and using QI methods to improve it
Verma AA, Trbovich P, Mamdani M, Shojania KG. Grand rounds in methodology: key considerations for implementing machine learning solutions in quality improvement initiatives. BMJ Qual Saf. 2024;33(2):121-131. Doi:10.1136/bmjqs-2022-015713
Smith M, Sattler A, Hong G, Lin S. From Code to Bedside: Implementing Artificial Intelligence Using Quality Improvement Methods. J Gen Intern Med. 2021 Apr;36(4):1061-1066. doi: 10.1007/s11606-020-06394-w. Epub 2021 Jan 19. PMID: 33469745; PMCID: PMC8041947.
Feng J, Phillips RV, Malenica I, Bishara A, Hubbard AE, Celi LA, Pirracchio R. Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare. NPJ Digit Med. 2022 May 31;5(1):66. doi: 10.1038/s41746-022-00611-y. PMID: 35641814; PMCID: PMC9156743.
Fahim YA, Hasani IW, Kabba S, Ragab WM. Artificial intelligence in healthcare and medicine: clinical applications, therapeutic advances, and future perspectives. Eur J Med Res. 2025 Sep 23;30(1):848. doi: 10.1186/s40001-025-03196-w. PMID: 40988064; PMCID: PMC12455834.
Optional Reading for Peer Comparisons/Social Norms/Behavioral Economic Nudges
Tang MY, Rhodes S, Powell R, McGowan L, Howarth E, Brown B, Cotterill S. How effective are social norms interventions in changing the clinical behaviours of healthcare workers? A systematic review and meta-analysis. Implement Sci 2021 Jan7;16(1):8. doi:10.1186/s13012-020-01072-1.
Session Title: Advanced Statistical Process Control: Challenging Cases and How to Approach Them
Gupta M, Kaplan HC. Using Statistical Process Control to Drive Improvement in Neonatal Care: A Practical Introduction to Control Charts. Clinics in Perinatology, 2017 (NOTE: If you do not regularly use statistical process control in your QI work, this article can provide a reasonable overview of the methods to help you with this more advanced workshop)
Wheeler DJ. When Should We Compute New Limits? Quality Digest Daily, April 2, 2012.
Wheeler, DJ. So You Want to Use a p-Chart? Not all count-based data will qualify. Quality Digest Daily, October 4, 2021
Provost LP, Murray S. The Health Care Data Guide: Learning from Data for Improvement. 2nd edition. Jossey-Bass, 2022; Fixing and Revising Limits: Chapter 4 (pages 141-147) and Skewed Data: Chapter 9 (pages 355-360)
Session Title: Hands-On Statistical Process Control: Making Run Charts and Control Charts
Gupta M, Kaplan HC. Using Statistical Process Control to Drive Improvement in Neonatal Care: A Practical Introduction to Control Charts. Clinics in Perinatology, 2017
Perla RJ, Provost LP, Murray SK. The run chart: a simple analytical tool for learning from variation in healthcare processes. BMJ Quality & Safety, 2011
Provost LP, Murray S. The Health Care Data Guide: Learning from Data for Improvement. 2nd edition. Jossey-Bass, 2022, Chapters 3-5
