Family Input for Quality and Safety

Patient Safety Clinical Trial

— FIQS  

Official title:

Novel IT to Create Patient-Integrated Hospital Quality Improvement and Improve Patient Safety

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03202888
• Other study ID #: FIQS
• Status: Completed
• Phase: N/A
• Start date: June 26, 2017
• Est. completion date: April 27, 2018

Study information

• Verified date: October 2018
• Source: University of California, San Francisco
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

This project aims to create and evaluate a tool that gathers patient and family member feedback and makes it rapidly available to providers, enabling nimble and responsive safety and quality improvement efforts. Aim 1. Determine feasibility and acceptability of the patient data collection and provider dashboard tool. The investigators will conduct usability testing prior to study start, measure user (patients and providers) engagement over time, and gather feedback about the tool at study end. This will test the hypothesis that patient and caregiver characteristics will predict tool use. Aim 2. Assess whether reporting patient- and caregiver- observed processes of care to providers leads to changes over time. The investigators hypothesize that performance on structured items of interest will improve over time with rapidly available data presented to providers. Aim 3. Estimate tool implementation effect sizes, using a pre-post design, on medical errors.

Description:

More than a decade after the seminal Institute Of Medicine report, "To Err is Human", failure rates in patient safety remain stubbornly high in hospitals. Prior efforts to improve hospital quality have had relatively little impact, in part due to limited access to timely quality improvement data. The long-term goal of this application is to leverage existing technologies to give voice to hospitalized patients and their family members, leading to improvements in hospital safety and quality. The overall objective in this application is to create and evaluate a tool that gathers patient and family member feedback and makes it rapidly available to providers, enabling nimble and responsive safety and quality improvement efforts. The central hypothesis, based on the theory of co-production, is that observations from patients and families, gathered in a structured way, will provide actionable information regarding patient safety and quality. The rationale for doing this project is to test an innovative new approach to creating a rapidly available data stream to providers who are working on specific improvement efforts, and a mechanism for creating a quality improvement approach that is inherently patient-centered. The investigators plan to test the central hypothesis and thereby accomplish the objective of this application by focusing on the following areas of research for Health IT: Use, Implementation, and Impact on Outcomes, under the study type "Pilot and feasibility", pursuing three specific aims: Aim 1. Determine feasibility and acceptability of the patient data collection and provider dashboard tool (Use and Implementation). The investigators will conduct usability testing prior to study start, measure user (patients and providers) engagement over time, and gather feedback about the tool at study end. The investigators hypothesize that patient and caregiver characteristics will predict tool use. Aim 2. Assess whether reporting patient- and caregiver- observed processes of care to providers leads to changes over time (Implementation). The investigators hypothesize that performance on structured items of interest will improve over time with rapidly available data presented to providers. Aim 3. Estimate tool implementation effect sizes, using a pre-post design, on medical errors (Impact on outcomes). The proposed research is innovative, in the investigators' opinion, based on a paradigm-shifting conceptual model of patient-engaged quality improvement, and because it leverages technology to gather and present data in an unprecedented manner. The expected contribution of the proposed research will be an adapted tool that will gather meaningful and important data on patient safety and present it in an actionable way to providers and hospital leaders, resulting in a powerful data stream to fuel rapid improvements in patient safety. Pilot data from this proposal will inform the design of a future cluster-randomized trial of the new tool across multiple hospital systems. This contribution will be significant because it represents key steps towards a new approach to improving patient safety in the hospital.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 435
• Est. completion date: April 27, 2018
• Est. primary completion date: April 27, 2018
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• Patient and caregiver participants will be recruited from admitted patients and their family members on the medical-surgical units at UCSF's Benioff Children's Hospital during the study period.

• Eligible providers will be the participating hospitalists during the study period.

All nurse managers on the units and the patient safety and quality managers for the units will be eligible. All nurses will be eligible on the participating units.

Exclusion Criteria:

• Patients who are youth in the foster care system will not be eligible.

• Patients or parents/guardians who do not have smart phones will not be eligible.

There are no provider or nurse or quality manager exclusions.

Related Conditions & MeSH terms

• Patient Safety

Intervention

Behavioral:
• Intervention
QuesGen-created mobile responsive website tool, Family Input for Quality and Safety.

Locations

Country	Name	City	State
United States	UCSF Benioff Children's Hospital	San Francisco	California

Sponsors (1)

Lead Sponsor	Collaborator
University of California, San Francisco

Country where clinical trial is conducted

United States, 

References & Publications (15)

Bardach NS, Asteria-Peñaloza R, Boscardin WJ, Dudley RA. The relationship between commercial website ratings and traditional hospital performance measures in the USA. BMJ Qual Saf. 2013 Mar;22(3):194-202. doi: 10.1136/bmjqs-2012-001360. Epub 2012 Nov 23. — View Citation

Blumenthal D, McGinnis JM. Measuring Vital Signs: an IOM report on core metrics for health and health care progress. JAMA. 2015 May 19;313(19):1901-2. doi: 10.1001/jama.2015.4862. — View Citation

Chassin MR. Improving the quality of health care: what's taking so long? Health Aff (Millwood). 2013 Oct;32(10):1761-5. doi: 10.1377/hlthaff.2013.0809. — View Citation

Clancy CM. Patient Safety: One Decade after To Err Is Human. 2009; http://www.psqh.com/septemberoctober-2009/234-september-october-2009-ahrq.html. Accessed October 29, 2013.

Classen DC, Resar R, Griffin F, Federico F, Frankel T, Kimmel N, Whittington JC, Frankel A, Seger A, James BC. 'Global trigger tool' shows that adverse events in hospitals may be ten times greater than previously measured. Health Aff (Millwood). 2011 Apr;30(4):581-9. doi: 10.1377/hlthaff.2011.0190. Erratum in: Health Aff (Millwood). 2011 Jun;30(6):1217. — View Citation

Conway PH, Mostashari F, Clancy C. The future of quality measurement for improvement and accountability. JAMA. 2013 Jun 5;309(21):2215-6. doi: 10.1001/jama.2013.4929. — View Citation

Erasmus V, Daha TJ, Brug H, Richardus JH, Behrendt MD, Vos MC, van Beeck EF. Systematic review of studies on compliance with hand hygiene guidelines in hospital care. Infect Control Hosp Epidemiol. 2010 Mar;31(3):283-94. doi: 10.1086/650451. Review. — View Citation

Greaves F, Pape UJ, King D, Darzi A, Majeed A, Wachter RM, Millett C. Associations between Internet-based patient ratings and conventional surveys of patient experience in the English NHS: an observational study. BMJ Qual Saf. 2012 Jul;21(7):600-5. doi: 10.1136/bmjqs-2012-000906. Epub 2012 Apr 20. — View Citation

Greaves F, Pape UJ, King D, Darzi A, Majeed A, Wachter RM, Millett C. Associations between Web-based patient ratings and objective measures of hospital quality. Arch Intern Med. 2012 Mar 12;172(5):435-6. doi: 10.1001/archinternmed.2011.1675. Epub 2012 Feb 13. — View Citation

Guide to Patient and Family Engagement: Environmental Scan Report. October 2014; http://www.ahrq.gov/research/findings/final-reports/ptfamilyscan/ptfamilysum.html. Accessed June 10, 2015.

Han E, Hudson Scholle S, Morton S, Bechtel C, Kessler R. Survey shows that fewer than a third of patient-centered medical home practices engage patients in quality improvement. Health Aff (Millwood). 2013 Feb;32(2):368-75. doi: 10.1377/hlthaff.2012.1183. — View Citation

James JT. A new, evidence-based estimate of patient harms associated with hospital care. J Patient Saf. 2013 Sep;9(3):122-8. doi: 10.1097/PTS.0b013e3182948a69. Review. — View Citation

Landrigan CP, Parry GJ, Bones CB, Hackbarth AD, Goldmann DA, Sharek PJ. Temporal trends in rates of patient harm resulting from medical care. N Engl J Med. 2010 Nov 25;363(22):2124-34. doi: 10.1056/NEJMsa1004404. Erratum in: N Engl J Med. 2010 Dec 23;363(26):2573. — View Citation

Rossi P, Lipsey M, Freeman H. Evaluation: A Systematic Approach. 7th Edition ed: SAGE Publications, Inc; 2003.

Shekelle PG, Pronovost PJ, Wachter RM, Taylor SL, Dy SM, Foy R, Hempel S, McDonald KM, Ovretveit J, Rubenstein LV, Adams AS, Angood PB, Bates DW, Bickman L, Carayon P, Donaldson L, Duan N, Farley DO, Greenhalgh T, Haughom J, Lake ET, Lilford R, Lohr KN, Meyer GS, Miller MR, Neuhauser DV, Ryan G, Saint S, Shojania KG, Shortell SM, Stevens DP, Walshe K. Advancing the science of patient safety. Ann Intern Med. 2011 May 17;154(10):693-6. doi: 10.7326/0003-4819-154-10-201105170-00011. — View Citation

* Note: There are 15 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Change in rate of preventable medical errors or adverse events per 100 admissions	This is a hospital unit-level outcome measure, assessing unit-level rate of adverse events and preventable medical errors in a time period before the intervention, and the unit-level rate at the end of the intervention. The investigators will apply standard definitions of medical errors as preventable failures in processes of care and adverse events as preventable and non-preventable unintended consequences of medical care that lead to patient harm. This is a composite measure and will be measured as total count of medical errors plus total count of adverse events per 100 admissions. The investigators will not track this measure across the same group of patients in the before and after periods. Participants will be included for the duration of their admission, which may vary. The rate will be measured cross-sectionally in both time periods.	Measured cross-sectionally in the hospital unit at baseline for three months, and again for three months at the end of the intervention (months 10,11,12 of the intervention).