
==== Front
Perm J
tpj
tpj
The Permanente Journal
1552-5767
1552-5775
The Permanente Press

39267443
10.7812/TPP/24.125
TPJ-24-125
Editorial
Improving Human Experience in Health Care: Now More Than Ever, We Must Focus on People
http://orcid.org/0000-0002-7399-622X
Oliver Brant J PhD, MS, MPH, FNP-BC, PMHNP-BC 1 2 3
1 Office of Care Experience, the Value Institute, Dartmouth Health, Lebanon, NH, USA
2 Chronic Health Improvement Research Program at Dartmouth Health, Lebanon, NH, USA
3 Departments of Community & Family Medicine, the Dartmouth, Institute for Health Policy & Clinical Practice and Psychiatry, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
Brant J Oliver, PhD, MS, MPH, FNP-BC, PMHNP-BC brant.j.oliver@dartmouth.edu
2024
13 9 2024
28 3 195199
© 2024 The Authors.
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Published by The Permanente Federation LLC under the terms of the CC BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.
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pmcFollowing the seminal reports on health care quality and safety in the United States,1,2 there have been substantial efforts made toward developing the field of health care quality, development of the fields of implementation and complexity sciences,3,4 and efforts to improve health care quality and related outcomes in the United States and internationally. This has included the work of the Institute for Healthcare Improvement5 and patches of success realized by a number of organized improvement efforts (of which only a partial list are referenced here).6–12 However, after nearly three decades of work, we have not realized substantive population-level improvements in the key areas of the Institute for Healthcare Improvement’s Quadruple Aim,13 which encompasses outcomes (e.g. mortality, life expectancy, etc.), cost, patient experience, and workforce experience. Health care in the United States continues to become more expensive and less welcoming for the people engaging with it.14 Workforce engagement, burnout, and turnover are particularly concerning issues, with many health professionals leaving the workforce as health systems struggle to meet access demands of the populations they serve.15 Technological advances such as artificial intelligence (AI) may offer promising new possibilities, but also create new concerns and the need for ethical governance.16 The AI revolution also calls to memory many of the great promises made by past technological breakthroughs (such as the electronic health record) that have not yet been fully realized.17

Major implementation science frameworks,18,19 and hybrid improvement and implementation approaches20 reinforce earlier thinking from clinical microsystems21 theory and more recent arguments from the developing sciences of learning health systems (LHS)22 and health care coproduction,23 namely that a priority focus must be placed on the contexts in which the work is happening and the people interacting with it. Yet, a majority of our efforts, resources, and scholarship in the field has been focused on the mechanistic, procedural, process, and technological aspects of improvement, and comparatively less focused on the people involved.24 Many quality and safety frameworks, value models, and measurement approaches25–28 include a focus on people by measuring patient experience, satisfaction, and engagement, but in practice, “people” and “experience” aspects have often come second to process improvement and cost containment. More recently, the Beryl Institute has defined the field of human experience29 and developed a new value argument for prioritizing it in health care.30 These efforts build upon the field of patient and family centered-care31 and align closely with developing the field of health care coproduction.32 The general thrust of these efforts calls to question the failure of our improvement efforts to change health care quality and outcomes over the past 30 years and suggests that it is time to place a new priority on improving human experience in health care.

Clark et al’s commentary frames this discussion across the nine articles in this special section of The Permanente Journal by highlighting four areas that will be of critical importance for the future of health care quality: (1) LHS; (2) coproduction of health care service; (3) AI; and (4) workforce development. Learning health (LH) approaches (such as LHS,22 coproduction LHS (CLHS),33 learning health networks,34 and learning health organizations35) have promise to bring health systems to life in ways not previously possible by simultaneously accelerating the ability to conduct, improve, and study work (conduct research). Although technological advances in informatics and data science are bringing integrated LH approaches within reach, the science is not yet fully developed.36 The scoping review by Davis et al describes significant variation in LH efforts in complex, chronic, and costly conditions. Few have yet fully realized ideal development.

It was not that long ago that the electronic health record was touted as a new great technological advancement in health care,17 and now AI is emerging as the great new technological hope for our future.37,38 An AI-enabled future could mean better access, progress notes that are automatically written for busy clinicians, and wearable devices that feed data forward to inform precision medicine and facilitate better self-monitoring and motivate better health behaviors. These are but a few aspects of what Clark et al describe as “beneficial AI”—applications of AI that can improve our work and eliminate tasks that distract us from meaningful human interactions with patients, families, and our workforce. However, there is also a risk that the opposite could happen if we are not thoughtful in our stewardship. Groups such as RAISE (Responsible AI for Social and Ethical Health)39 and others16 are rushing to define ethical and meaningful use criteria and guidelines to help govern AI use and prevent applications that could demoralize the health care workforce, overtake provider autonomy, and game the health care system for the financial gain of commercial interests. Poorly applied AI could also fail to meaningfully include disadvantaged populations in the data or algorithms it uses. The brief report by Verkhovsky et al describes inequities in outcomes for low English proficiency persons in rural health care, highlighting how important it is to address disparities as a general priority and that disparities could become amplified by poorly designed or poorly implemented AI approaches.

Coproduction may provide a counterbalance to the burgeoning technology revolution in health care. Coproduction theory argues that health care is often a service, and not always a product, and requires two parties (a professional and a patient or care partner) to create health care together.23 , 40As the newest iteration of health care quality,41 it brings a renewed focus to the people involved in health and care, and creates a pathway by which human experience could become a priority focus in improvement work. However, coproduction is challenged by its struggles to define itself practically and establish how it can increase quality and value. CO-VALUE42,43 is an international community of practice that has been engaged in exploring, defining, and assessing coproduction value creation since 2019. Forcino et al report in this special section on the development of coproduction value domains, which have been recently identified by this group. Meaningful empowerment of patient voice in learning health approaches will be critically important in bringing coproduction into practice at scale,44 and the use of patient-reported outcome measures and patient-reported experience measuresin LH approaches can be leveraged to inform improvement in new ways.45 Clark et al, describe an application of positive deviance theory,46 which uses compliments received by patients and families to inform improvement strategy and prioritizations efforts. Oliver et al offer a new Markov modeling–informed47 statistical process control48 analytical approach, which uses patient reported outcomes data on emergency and hospitalization utilization to predict cost differences to inform improvement work at the pace that it is happening in real-world settings—and from the perspective of patients.

None of this will be achievable without the most important element—our health care workforce. Our workforce has perhaps never been under more pressure, more susceptible to burnout, or more likely to leave health care than it is now. We must create opportunity spaces for them and their work, and create opportunities for improvement to flourish. To do this, we must skillfully employ methods that can empower this work and create communities of practice for those engaged in it, such as learning collaboratives,49,50 clinician-driven performance improvement,51 coach-supported improvement,52 and coproduction-driven approaches.53 This includes professional development approaches to build capability in the workforce that are practical and feasible to access in today’s busy and complex health care environment. The practical approach developed by Oliver et al describes a new basic skills training program in shared decision-making (SDM), an important coproduction activity, for busy clinicians who are novices in SDM. Alexander et al describe knowledge and skills results of four practical approach training programs conducted in oncology and multiple sclerosis contexts. Hakim et al provide an in-depth qualitative analysis of learner experience (feasibility, acceptability, and utility) from an oncology team that engaged in the practical approach program.

In her recent book, Who do we choose to be? Facing reality, claiming leadership, restoring sanity, Margaret Wheatley calls for us to become “warriors for the human spirit,” professionals who are committed to protecting, nurturing, and sustaining the human spirit as we drive forward into a technologically complex future characterized by political strife and climate change.54 In health care, these warriors will be called upon to wield the tools of technology and coproduction and build LHSs that are not only intelligent but also kind, safe, and trustworthy. In their book, Intelligent Kindness, Ballatt, Campling, and Maloney call upon us to reestablish relationships and kinship in our work.55 This aligns closely with what Jason Wolf of the Beryl Institute argues in his recent book, Transforming the Future of Healthcare 56—namely that there must be a fundamental shift from the transactional to the relational work in health care.

If we are indeed to become health care warriors for the future, as Wheatley suggests, we must charge into that future with a steadfast commitment and knowledge of who we are fighting for. To improve upon our past, health care improvement must remember first and foremost that health and care are for and about people. If we get that right, the rest is likely to follow.
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References

1. Institute of Medicine (US) Committee on Quality of Health Care in America Crossing the Quality Chasm: A New Health System for the 21st Century [Washington (DC): National Academies Press (US]. 2001.
2. Kohn LT , Corrigan JM , Donaldson MS , eds. Committee on quality of health care in america. to err is human: Building a safer health system. Institute of Medicine. 2000.
3. Brownson RC , Colditz GA , Proctor EK , eds. Dissemination and implementation research in health: Translating science to practice. Oxford University Press; 2000.
4. Frankel SA , Thurber SD , Bourgeois JA . Complexity in Health Care. In: Complexity in health care: A paradigm shift for clinical practice. Springer; 2023. 10.1007/978-3-031-14949-8
5. Institute for Healthcare Improvement. Accessed 15 July 2024. www.ihi.org
6. Edwards EM , Ehret DEY , Soll RF , Horbar JD . Vermont oxford network: A worldwide learning community. Transl Pediatr. 2019;8 (3 ):182–192. 10.21037/tp.2019.07.01 31413952
7. Melmed GY , Oliver BJ , Hou JK , et al. Quality of care program reduces unplanned health care utilization in patients with inflammatory bowel disease. Am J Gastroenterol. 2021;116 (12 ):2410–2418. 10.14309/ajg.0000000000001547 34797226
8. James BC . The cystic fibrosis improvement story: We count our successes in lives BMJ quality & safety published online first. 2014. 10.1136/bmjqs-2014-002839
9. Stevens DP , Marshall BC . A decade of healthcare improvement in cystic fibrosis: Lessons for other chronic diseases. BMJ Qual Saf. 2014;23 (Suppl 1 ):i1–i2. 10.1136/bmjqs-2014-002871
10. Plsek PE . Accelerating Health Care Transformation with Lean and Innovation. CRC Press; 2013. 10.1201/b15817
11. McHugh MD , Aiken LH , Eckenhoff ME , Burns LR . Achieving Kaiser Permanente quality. Health Care Manage Rev. 2016;41 (3 ):178–188. 10.1097/HMR.0000000000000070 26131607
12. Gottlieb K . The Nuka System of Care: Improving health through ownership and relationships. Int J Circumpolar Health. 2013;72 . 10.3402/ijch.v72i0.21118
13. The Triple Aim or the Quadruple Aim? Four Points to Help Set Your Strategy. Accessed 22 July 2024. https://www.ihi.org/insights/triple-aim-or-quadruple-aim-four-points-help-set-your-strategy
14. MacGillivray TE . Advancing the culture of patient safety and quality improvement. Methodist Debakey Cardiovasc J. 2020;16 (3 ):192–198. 10.14797/mdcj-16-3-192 33133354
15. Murthy VH . Confronting health worker burnout and well-being. N Engl J Med. 2022;387 (7 ):577–579. 10.1056/NEJMp2207252 35830683
16. Sim I , Cassel C . The ethics of relational AI - expanding and implementing the belmont principles. N Engl J Med. 2024;391 (3 ):193–196. 10.1056/NEJMp2314771 39007542
17. Honavar SG . Electronic medical records - the good, the bad and the ugly. Indian J Ophthalmol. 2020;68 (3 ):417–418. 10.4103/ijo.IJO_278_20 32056991
18. Damschroder LJ , Reardon CM , Widerquist MAO , Lowery J . The updated consolidated framework for implementation research based on user feedback. Implement Sci. 2022;17 (1 ). 10.1186/s13012-022-01245-0
19. Holtrop JS , Estabrooks PA , Gaglio B , et al. Understanding and applying the RE-AIM framework: Clarifications and resources. J Clin Transl Sci. 2021;5 (1 ). 10.1017/cts.2021.789
20. Ramaswamy R , Reed J , Livesley N , et al. Unpacking the black box of improvement. Int J Qual Health Care. 2018;30 (suppl_1 ):15–19. 10.1093/intqhc/mzy009 29462325
21. Likosky DS . Clinical microsystems: A critical framework for crossing the quality chasm. J Extra Corpor Technol. 2014;46 (1 ):33–37.24779117
22. Learning Health Systems. Accessed 15 July 2024. https://www.ahrq.gov/learning-health-systems/about.html
23. Batalden M , Batalden P , Margolis P , et al. Coproduction of healthcare service. BMJ Qual Saf. 2016;25 (7 ):509–517. 10.1136/bmjqs-2015-004315
24. Pomare C , Mahmoud Z , Vedovi A , et al. Learning health systems: A review of key topic areas and bibliometric trends. Learn Health Syst. 2021;6 (1 ):e10265. 10.1002/lrh2.10265 35036549
25. Six domains of healthcare quality. Accessed 15 July 2024. https://www.ahrq.gov/talkingquality/measures/six-domains.html
26. Martin L , Nelson E , Rakover J , Chase A . Whole system measures 2.0: A compass for health system leaders. Institute for Healthcare Improvement; 2016.
27. Nelson EC , Mohr JJ , Batalden PB , Plume SK . Improving health care, Part 1: The clinical value compass. The Joint Commission Journal on Quality Improvement. 1996;22 (4 ):243–258. 10.1016/S1070-3241(16)30228-0 8743061
28. Berwick DM , Nolan TW , Whittington J . The Triple Aim: Care, health, and cost. Health Affairs. 2008;27 (3 ):759–769. 10.1377/hlthaff.27.3.759 18474969
29. Defining Patient and Human Experience. Accessed July 2024. https://theberylinstitute.org/defining-patient-experience
30. Wolf JA , Bhalla V , Carlson B , et al. Investing in the bottom line: The value case for improving human experience in healthcare. Patient Experience Journal. 2024;11 (1 ):14–20. 10.35680/2372-0247.1938
31. What is patient and family centered care? [website]. In: Institute for Patient and Family-Centered Care. Accessed July 22, July 2024. https://www.ipfcc.org/about/pfcc.html
32. Elwyn G , Nelson E , Hager A , Price A . Coproduction: When users define quality. BMJ Qual Saf. 2020;29 (9 ):711–716. 10.1136/bmjqs-2019-009830
33. The Dartmouth Coproduction Learning Health System Model [website]. In: Dartmouth Coproduction Laboratory. Accessed July 22, July 2024. https://sites.dartmouth.edu/coproduction/our-model
34. Cincinnati Children’s Anderson Center [website]. In: Learning Health Networks. Accessed July 22, July 2024. https://www.cincinnatichildrens.org/research/divisions/j/anderson-center/learning-networks
35. Senge PM . The Fifth Discipline: The art and science of the Learning Organization. Random House; 2006.
36. Ellis LA , Sarkies M , Churruca K , et al. Correction: The science of Learning Health Systems: Scoping review of empirical research. JMIR Med Inform. 2022;10 (8 ). 10.2196/41424
37. Kohane IS , Beam AL , Manrai AK . Why medicine must become a knowledge-processing discipline. NEJM. 2024;1 (7 ). 10.1056/AIp2400582
38. Tierney AA , Gayre G , Hoberman B , et al. Ambient artificial intelligence scribes to alleviate the burden of clinical documentation. NEJM Catalyst. 2024;5 (3 ). 10.1056/CAT.23.0404
39. Responsible AI for safe and equitable health (RAISE). Accessed 22 July 2024. https://med.stanford.edu/raisehealth
40. Batalden PB . Getting more health from healthcare: Quality improvement must acknowledge patient coproduction—an essay by Paul Batalden. BMJ. 2018;362 . 10.1136/bmj.k3617
41. Batalden P , Foster T . From assurance to coproduction: A century of improving the quality of health-care service. Int J Qual Health Care. 2021;33 (Supplement_2 ):ii10–ii14. 10.1093/intqhc/mzab059 34849968
42. Oliver BJ , Batalden PB , DiMilia PR , et al. Coproduction value creation in healthcare service (CO-VALUE): An international multicentre protocol to describe the application of a model of value creation for use in systems of coproduced healthcare services and to evaluate the initial feasibility, utility and acceptability of associated system-level value creation assessment approaches. BMJ Open. 2020;10 (10 ). 10.1136/bmjopen-2020-037578
43. Oliver BJ , Forcino RC , Batalden PB . Initial development of a self-assessment approach for coproduction value creation by an international community of practice. Int J Qual Health Care. 2021;33 (Supplement_2 ):ii48–ii54. 10.1093/intqhc/mzab077 34849960
44. Gremyr A , Andersson Gäre B , Thor J , Elwyn G , Batalden P , Andersson AC . The role of co-production in Learning Health Systems. Int J Qual Health Care. 2021;33 (Supplement_2 ):ii26–ii32. 10.1093/intqhc/mzab072 34849971
45. Oliver BJ , Nelson E , Kerrigan CK . Turning “Feed-Forward” patient reported outcomes (PRO) data into information to take intelligent action and improve outcomes: Case studies and principles to aid score interpretation and care planning. Med Care. 2019;57 (5 ):S31–S37. 10.1097/MLR.0000000000001088 30985594
46. Kassie AM , Eakin E , Abate BB , et al. The use of Positive Deviance approach to improve health service delivery and quality of care: A scoping review. BMC Health Serv Res. 2024;24 (1 ). 10.1186/s12913-024-10850-2
47. Almario CV , Kogan L , van Deen WK , et al. Health economic impact of a multicenter quality-of-care initiative for reducing unplanned healthcare utilization among patients with inflammatory bowel disease. Am J Gastroenterol. 2021;116 (12 ):2459–2464. 10.14309/ajg.0000000000001540 34730561
48. Oliver BJ , Ogrinc G , eds. Statistical Process Control (SPC) for Continuous and Attribute Data, pp. 77-113.. In: Practical Measurement for Healthcare Improvement. Joint Commission Resources. ISBN: 978-1635853063 .
49. Gotham HJ , Paris M , Hoge MA . Learning collaboratives: A strategy for quality improvement and implementation in behavioral health. J Behav Health Serv Res. 2023;50 (2 ):263–278. 10.1007/s11414-022-09826-z 36539679
50. Godfrey MM , Oliver BJ . Accelerating the rate of improvement in cystic fibrosis care: Contributions and insights of the learning and leadership collaborative. BMJ Qual Saf. 2014;23 (Suppl 1 ):i23–i32. 10.1136/bmjqs-2014-002804
51. Goitein L . Clinician-directed performance improvement: Moving beyond externally mandated metrics. Health Affairs. 2020;39 (2 ):264–272. 10.1377/hlthaff.2019.00505 32011946
52. Carney PA , Dickinson WP , Fetter J , et al. An exploratory mixed methods study of experiences of interprofessional teams who received coaching to simultaneously redesign primary care education and clinical practice. J Prim Care Community Health. 2021;12 . 10.1177/21501327211023716
53. Tosteson ANA , Kirkland KB , Holthoff MM , et al. Harnessing the collective expertise of patients, care partners, clinical teams, and researchers through a coproduction learning health system: A case study of the dartmouth health promise partnership. J Ambul Care Manage. 2023;46 (2 ):127–138. 10.1097/JAC.0000000000000460 36820633
54. Wheatley MJ . Who do we choose to be? facing reality, claiming leadership, restoring sanity. 2nd ed. Berret-Koehler Publishers
55. Ballatt J , Campling P , Maloney C . Intelligent kindness: Rehabilitating the welfare state. 2nd Ed. Cambridge University Press; 2020. 10.1017/9781911623236
56. Wolf JA . Transforming the future of healthcare: Reflections on a decade of the experience Movement. In: Jason A Wolf; 2024.
