Perceived Burden Due to Registrations for Quality Monitoring and Improvement in Hospitals: A Mixed Methods Study

Document Type : Original Article

Authors

1 Department of Intensive Care, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands

2 Scientific Center for Quality of Healthcare, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands

3 Centre of Expertise on Quality and Safety, University Medical Centre Groningen, Groningen, The Netherlands

4 Department of Quality and Safety, Rijnstate Hospital, Arnhem, The Netherlands

Abstract

Background
Quality indicators are registered to monitor and improve the quality of care. However, the number and effectiveness of quality indicators is under debate, and may influence the joy in work of physicians and nurses. Empirical data on the nature and consequences of the registration burden are lacking. The aim of this study was to identify and explore healthcare professionals’ perceived burden due to quality registrations in hospitals, and the effect of this burden on their joy in work.
 
Methods
A mixed methods observational study, including participative observations, a survey and semi-structured interviews in two academic hospitals and one teaching hospital in the Netherlands. Study participants were 371 healthcare professionals from an intensive care unit (ICU), a haematology department and others involved in the care of elderly patients and patients with prostate or gastrointestinal cancer.
 
Results
On average, healthcare professionals spend 52.3 minutes per working day on quality registrations. The average number of quality measures per department is 91, with 1380 underlying variables. Overall, 57% are primarily registered for accountability purposes, 19% for institutional governance and 25% for quality improvement objectives. Only 36% were perceived as useful for improving quality in everyday practice. Eight types of registration burden were identified, such as an excessive number of quality registrations, and the lack of usefulness for improving quality and inefficiencies in the registration process. The time healthcare professionals spent on quality registrations was not correlated with any measure of joy in work. Perceived unreasonable registrations were negatively associated with healthcare professionals’ joy in work (intrinsic motivation and autonomy). Healthcare professionals experienced quality registrations as diverting time from patient care and from actually improving quality.
 
Conclusion
Registering fewer quality indicators, but more of what really matters to healthcare professionals, is key to increasing the effectiveness of registrations for quality improvement and governance. Also the efficiency of quality registrations should be increased through staffing and information and communications technology solutions to reduce the registration burden experienced by nurses and physicians.

Highlights

 

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Commentaries Published on this Paper

  • Complex Governance Does Increase Both the Real and Perceived Registration Burden: The Case of the Netherlands; Comment on “Perceived Burden Due to Registrations for Quality Monitoring and Improvement in Hospitals: A Mixed Methods Study”

          Abstract | PDF

 

  • More Evidence That the Healthcare Administrative Burden Is Real, Widespread and Has Serious Consequences; Comment on “Perceived Burden Due to Registrations for Quality Monitoring and Improvement in Hospitals: A Mixed Methods Study”

        Abstract | PDF

 

  •  Purpose, Subject, and Consumer; Comment on “Perceived Burden Due to Registrations for Quality Monitoring and Improvement in Hospitals: A Mixed Methods Study”

        Abstract | PDF

 

Authors' Response to the Commentaries

  • Time to See Quality Measurement Differently: Focus on Reflection, Learning and Improvement; A Response to the Recent Commentaries

          Abstract | PDF

Keywords

References

  1. Donabedian A. Explorations in Quality Assessment and Monitoring. Ann Arbor, Michigan: Health Administration Press; 1980.
  2. Balding C. From quality assurance to clinical governance. Aust Health Rev. 2008;32(3):383-391. doi:10.1071/ah080383
  3. Walshe K. The rise of regulation in the NHS. BMJ. 2002;324(7343):967-970. doi:10.1136/bmj.324.7343.967
  4. Fung CH, Lim YW, Mattke S, Damberg C, Shekelle PG. Systematic review: the evidence that publishing patient care performance data improves quality of care. Ann Intern Med. 2008;148(2):111-123. doi:10.7326/0003-4819-148-2-200801150-00006
  5. Meyer GS, Nelson EC, Pryor DB, et al. More quality measures versus measuring what matters: a call for balance and parsimony. BMJ Qual Saf. 2012;21(11):964-968. doi:10.1136/bmjqs-2012-001081
  6. Cunningham L, Kennedy J, Nwolisa F, Callard L, Wike C. Patients not paperwork-bureaucracy affecting nurses in the NHS. London: NHS Institute for Innovation and Improvement; 2012.
  7. Ontregel de zorg. https://www.ordz.nl/.  Accessed June 5, 2019.
  8. Meurs PL, Kremer JAM, van de Gevel BJC, Schot EJJ. Trust Well Earned: A New Approach to Accountability for Better Healthcare. https://www.raadrvs.nl/documenten/publications/2019/5/14/trust-well-earned-a-new-approach-to-accountability-for-better-healthcare.  Updated 2019. Accessed June 5, 2019.
  9. Schippers EI. Kamerbrief over merkbaar minder regeldruk. Ministerie van Volksgezondheid, Welzijn en Sport; July 2, 2015.
  10. Saver BG, Martin SA, Adler RN, et al. Care that matters: quality measurement and health care. PLoS Med. 2015;12(11):e1001902. doi:10.1371/journal.pmed.1001902
  11. de Vos M, Graafmans W, Kooistra M, Meijboom B, Van Der Voort P, Westert G. Using quality indicators to improve hospital care: a review of the literature. Int J Qual Health Care. 2009;21(2):119-129. doi:10.1093/intqhc/mzn059
  12. Ballard A. Framing bias in the interpretation of quality improvement data: evidence from an experiment. Int J Health Policy Manag. 2019;8(5):307-314. doi:10.15171/ijhpm.2019.08
  13. Freeman T. Using performance indicators to improve health care quality in the public sector: a review of the literature. Health Serv Manage Res. 2002;15(2):126-137. doi:10.1258/0951484021912897
  14. Shaw J, Taylor R, Dix K. Uses and Abuses of Performance Data in Healthcare. Vol 40. London: Dr Foster; 2015.
  15. Berenson RA, Rice T. Beyond measurement and reward: methods of motivating quality improvement and accountability. Health Serv Res. 2015;50 Suppl 2(Suppl 2):2155-2186. doi:10.1111/1475-6773.12413
  16. Veenstra GL, Dabekaussen K, Molleman E, Heineman E, Welker GA. Health care professionals' motivation, their behaviors, and the quality of hospital care: a mixed-methods systematic review. Health Care Manage Rev. 2020. doi:10.1097/hmr.0000000000000284
  17. Franco LM, Bennett S, Kanfer R. Health sector reform and public sector health worker motivation: a conceptual framework. Soc Sci Med. 2002;54(8):1255-1266. doi:10.1016/s0277-9536(01)00094-6
  18. Perlo J, Balik B, Swensen S, Kabcenell A, Landsman J, Feeley D. IHI Framework for Improving Joy in Work. Cambridge, Massachusetts: Institute for Healthcare Improvement; 2017.
  19. Shantz A, Alfes K, Arevshatian L. HRM in healthcare: the role of work engagement. Pers Rev. 2016;45(2):274-295. doi:10.1108/pr-09-2014-0203
  20. Swensen S, Shanafelt T, Mohta NS. Leadership Survey: Why Physician Burnout is Endemic, and How Health Care Must Respond. NEJM Catalyst Insights Report; 2016:3-12.
  21. Cañadas-De la Fuente GA, Vargas C, San Luis C, García I, Cañadas GR, De la Fuente EI. Risk factors and prevalence of burnout syndrome in the nursing profession. Int J Nurs Stud. 2015;52(1):240-249. doi:10.1016/j.ijnurstu.2014.07.001
  22. Del Carmen MG, Herman J, Rao S, et al. Trends and factors associated with physician burnout at a multispecialty academic faculty practice organization. JAMA Netw Open. 2019;2(3):e190554. doi:10.1001/jamanetworkopen.2019.0554
  23. Rao SK, Kimball AB, Lehrhoff SR, et al. The impact of administrative burden on academic physicians: results of a hospital-wide physician survey. Acad Med. 2017;92(2):237-243. doi:10.1097/acm.0000000000001461
  24. Erickson SM, Rockwern B, Koltov M, McLean RM. Putting patients first by reducing administrative tasks in health care: a position paper of the American College of Physicians. Ann Intern Med. 2017;166(9):659-661. doi:10.7326/m16-2697
  25. Blume LH, van Weert NJ, Delnoij DM. How to manage external demands in hospitals--the case of atrium MC. Healthc (Amst). 2015;3(3):157-159. doi:10.1016/j.hjdsi.2015.03.003
  26. Nicolaisen A, Bogh SB, Churruca K, Ellis LA, Braithwaite J, von Plessen C. Managers' perceptions of the effects of a national mandatory accreditation program in Danish hospitals. A cross-sectional survey. Int J Qual Health Care. 2019;31(5):331-337. doi:10.1093/intqhc/mzy174
  27. Casalino LP, Nicholson S, Gans DN, et al. What does it cost physician practices to interact with health insurance plans? Health Aff. 2009;28(Suppl 1):w533-w543. doi:10.1377/hlthaff.28.4.w533
  28. Himmelstein DU, Jun M, Busse R, et al. A comparison of hospital administrative costs in eight nations: US costs exceed all others by far. Health Aff (Millwood). 2014;33(9):1586-1594. doi:10.1377/hlthaff.2013.1327
  29. Pope C, Mays N. Qualitative Research in Health Care. Hoboken, United States: Wiley-Blackwell; 2006.
  30. Semmer NK, Tschan F, Meier LL, Facchin S, Jacobshagen N. Illegitimate tasks and counterproductive work behavior. Appl Psychol. 2010;59(1):70-96. doi:10.1111/j.1464-0597.2009.00416.x
  31. Jacobshagen N. Illegitimate Tasks, Illegitimate Stressors: Testing a New Stressor-Strain Concept [dissertation]. Switzerland: University of Bern; 2006.
  32. Deci EL, Ryan RM. Self-determination theory: a macrotheory of human motivation, development, and health. Can Psychol. 2008;49(3):182-185. doi:10.1037/a0012801
  33. Gagné M, Forest J, Vansteenkiste M, et al. The multidimensional work motivation scale: validation evidence in seven languages and nine countries. Eur J Work Organ Psychol. 2015;24(2):178-196. doi:10.1080/1359432x.2013.877892
  34. Chen B, Vansteenkiste M, Beyers W, et al. Basic psychological need satisfaction, need frustration, and need strength across four cultures. Motiv Emot. 2015;39(2):216-236. doi:10.1007/s11031-014-9450-1
  35. Glaser BG, Strauss AL. The Discovery of Grounded Theory: Strategies for Qualitative Research. Chicago: Aldine Publishing Company; 1967.
  36. Lingard L, Albert M, Levinson W. Grounded theory, mixed methods, and action research. BMJ. 2008;337:a567. doi:10.1136/bmj.39602.690162.47
  37. Salanova M, Lorente L, Chambel MJ, Martínez IM. Linking transformational leadership to nurses' extra-role performance: the mediating role of self-efficacy and work engagement. J Adv Nurs. 2011;67(10):2256-2266. doi:10.1111/j.1365-2648.2011.05652.x
  38. O'Cathain A, Murphy E, Nicholl J. Three techniques for integrating data in mixed methods studies. BMJ. 2010;341:c4587. doi:10.1136/bmj.c4587
  39. Cho YI, Johnson TP, Vangeest JB. Enhancing surveys of health care professionals: a meta-analysis of techniques to improve response. Eval Health Prof. 2013;36(3):382-407. doi:10.1177/0163278713496425
  40. Galletta M, Portoghese I. Organizational citizenship behavior in healthcare: the roles of autonomous motivation, affective commitment and learning orientation. Rev Int Psychol Soc. 2012;25(3-4):121-145.
  41. van der Burgt SME, Kusurkar RA, Croiset G, Peerdeman SM. Exploring the situational motivation of medical specialists: a qualitative study. Int J Med Educ. 2018;9:57-63. doi:10.5116/ijme.5a83.6025
  42. Sinsky C, Tutty M, Colligan L. Allocation of physician time in ambulatory practice. Ann Intern Med. 2017;166(9):683-684. doi:10.7326/l17-0073
  43. de Vos M, Graafmans W, Keesman E, Westert G, van der Voort PH. Quality measurement at intensive care units: which indicators should we use? J Crit Care. 2007;22(4):267-274. doi:10.1016/j.jcrc.2007.01.002
  44. Botje D, Ten Asbroek G, Plochg T, et al. Are performance indicators used for hospital quality management: a qualitative interview study amongst health professionals and quality managers in The Netherlands. BMC Health Serv Res. 2016;16(1):574. doi:10.1186/s12913-016-1826-3
  45. Christino MA, Matson AP, Fischer SA, Reinert SE, Digiovanni CW, Fadale PD. Paperwork versus patient care: a nationwide survey of residents' perceptions of clinical documentation requirements and patient care. J Grad Med Educ. 2013;5(4):600-604. doi:10.4300/jgme-d-12-00377.1
  46. Exworthy M, Gabe J, Jones IR, Smith G. Professional autonomy and surveillance: the case of public reporting in cardiac surgery. Sociol Health Illn. 2019;41(6):1040-1055. doi:10.1111/1467-9566.12883
  47. Andersen LB, Kristensen N, Pedersen LH. Documentation requirements, intrinsic motivation, and worker absence. Int Public Manag J. 2015;18(4):483-513.
  48. Damschroder LJ, Robinson CH, Francis J, et al. Effects of performance measure implementation on clinical manager and provider motivation. J Gen Intern Med. 2014;29 Suppl 4:877-884. doi:10.1007/s11606-014-3020-9
  49. Pedersen LB, Andersen MKK, Jensen UT, Waldorff FB, Jacobsen CB. Can external interventions crowd in intrinsic motivation? a cluster randomised field experiment on mandatory accreditation of general practice in Denmark. Soc Sci Med. 2018;211:224-233. doi:10.1016/j.socscimed.2018.06.023
  50. Burnett S, Mendel P, Nunes F, et al. Using institutional theory to analyse hospital responses to external demands for finance and quality in five European countries. J Health Serv Res Policy. 2016;21(2):109-117. doi:10.1177/1355819615622655
  51. Shah A. Using data for improvement. BMJ. 2019;364:l189. doi:10.1136/bmj.l189
  52. Vaughn VM, Saint S, Krein SL, et al. Characteristics of healthcare organisations struggling to improve quality: results from a systematic review of qualitative studies. BMJ Qual Saf. 2019;28(1):74-84. doi:10.1136/bmjqs-2017-007573
  53. Jones L, Pomeroy L, Robert G, Burnett S, Anderson JE, Fulop NJ. How do hospital boards govern for quality improvement? a mixed methods study of 15 organisations in England. BMJ Qual Saf. 2017;26(12):978-986. doi:10.1136/bmjqs-2016-006433
  54. Pollitt C. Performance management 40 years on: a review. Some key decisions and consequences. Public Money Manag. 2018;38(3):167-174. doi:10.1080/09540962.2017.1407129
  55. Mannion R, Braithwaite J. Unintended consequences of performance measurement in healthcare: 20 salutary lessons from the English National Health Service. Intern Med J. 2012;42(5):569-574. doi:10.1111/j.1445-5994.2012.02766.x
  56. Mazur LM, Mosaly PR, Moore C, Marks L. Association of the usability of electronic health records with cognitive workload and performance levels among physicians. JAMA Netw Open. 2019;2(4):e191709. doi:10.1001/jamanetworkopen.2019.1709
  57. Registratie aan de bron. Architecture. The basic principles of health and care information models (HCIMs) and how they can be used. Volume 1. https://zibs.nl/images/4/44/HCIM_Architecture_Document_UK_v1.0.pdf.  Updated 2017. Accessed June 8, 2019.
  58. Khatri N, Brown GD, Hicks LL. From a blame culture to a just culture in health care. Health Care Manage Rev. 2009;34(4):312-322. doi:10.1097/HMR.0b013e3181a3b709
  59. Berwick DM, Loehrer S, Gunther-Murphy C. Breaking the rules for better care. JAMA. 2017;317(21):2161-2162. doi:10.1001/jama.2017.4703
International Journal of Health Policy and Management
Volume 11, Issue 2
February 2022
Pages 183-196

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History

  • Receive Date: 12 September 2019
  • Revise Date: 05 June 2020
  • Accept Date: 05 June 2020
  • First Publish Date: 01 February 2022

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