Clinical Predicators of Satisfaction Among Spine Patients: A Single Center Study NeuroSafe 2017 Breakout Presentation July 20-21, 2017 Rasheedat Zakare, BA Elise Seyferth, BA Oren Gottfried, MD
Overview Introduction Hypotheses Background Data & Methods Results Future Directions
Clinic Satisfaction Tool (CST) Implemented in January 2016 Motivation 2015 CG CAHPS scores showed physician communication below expectations Feedback on visit satisfaction from CG CAHPS has a long turn-around time and is only in de-identified, aggregated form Goals: Facilitate patient communication Improve visit satisfaction Provide real time feedback
Implementation Clinic Rounding Tool given to every patient at check in Patient fills out chief complaints before visit Physician reviews chief complaints during visit Patient gives clinic feedback Satisfaction Questions answered Suggestions for improvement Nurse reviews CRT before patient leaves If patient is unsatisfied or questions were unanswered, physician returns to address patient concerns
Chief complaints CST Data Fields Patient comments
Hypothesis #1 Chief complaints are associated with Primary outcome: visit diagnoses Secondary outcomes: visit, medical, and demographic information Isn t this obvious? Specific high-frequency chief complaints without a more serious secondary complaint in ED are not associated with emergent cases (Frei et al 2013) Baseline pain levels were higher in patients without a chief complaint among spine patients presenting for physiotherapy (Cook et al 2015) Ref 15,16
Hypothesis #2 Patient comments are associated with Primary outcome: visit diagnoses Secondary outcome: visit, medical, and demographic information Limited evidence Chronic psychiatric diseases are associated with lower satisfaction No relationship between diagnosis and satisfaction in ICU patients Ref 18,19
Why this matters I won the Doctor Lottery but only after some bad encounters. Donna Jackson Nakazawa May 27, 2017 Washington Post Ref 17
What is patient-centered research? Adapted from PCORI, 2013: Patient-Centered Outcomes Research (PCOR) helps people make informed healthcare decisions, allowing their voices to be heard in assessing the value of healthcare options. Assesses the benefits and harms of specific interventions to inform decision making; Includes individual preferences, focusing on outcomes that people care about such as symptoms and health-related quality of life. Incorporates a diversity of participants to address individual differences and barriers to implementation. Optimizes outcomes while addressing stakeholder perspectives. Ref 1
What is patient-centered research? Quality and outcomes research was originally under the purview of Natl Ctr for Health Services Research, but was separated out in 1989 as the Agency for Health Care Policy and Research Replaced by the Agency for Healthcare Quality and Research in 1999 Patient centered outcomes research became a separately funded priority in 2010 with the establishment of PCORI through the Affordable Care Act Ref 2
Why should neurosurgeons care? KPS You already do! NDI
Qualitative Data in Neurosurgery Interviews and surveys collect qualitative data Several validated scales and surveys are available for use Psychological assessment Functional recovery Quality of life Can provide important data about Patient resiliency & drivers of recovery after surgery Nonmedical drivers of patient satisfaction Gaps in understanding of patient perspectives Ref 3,4,5
Theoretical Frameworks Grand Surgeon uses their own experience to predict real-world phenomena Hypothesis may not fit the data at all! Validated scales and surveys capture only part of the patient experience Grounded Grounded theory starts from the ground up to create a model that is reflective of the real-life entity Ref 6,7
METHODS
Analysis Collected all CSTs from December 2016 Included: All CSTs from the first two weeks (12-1 to 12-9) All CSTs with comments from the rest of the month All data fields transcribed into RedCap database & unified with EMR data using 3-point identification Three-stage coding performed in NVivo
EMR Demographic data Gender, age, race Medical data Comorbidities Charlson Score, medications Visit data Visit provider & department, type of visit, diagnoses, procedures
Building a theoretical framework Using inductive reasoning to extract thematic elements from a body of text Stages of coding Open coding Identification of topics and themes within the text Axial coding Relating codes to each other in a thematic framework Selective coding Relating a code or group of codes to core elements Ref 8
RESULTS
Demographics Table 1: Spine Center Patient Demographics, All comers, December 2016 (n=1193) Age (mean, SD) 60.35 ± 14.2 Gender Male Female Race White Black Other 500 (41.9%) 693 (58.1%) 860 (72.1%) 251 (21.0%) 82 (6.9%) Current or former smoker 578 (48.7%) Department Neurosurgery Orthopedic Surgery PM & R 278 (23.3%) 274 (23.0%) 641 (53.7%) Comorbidities (mean, SD) 13.66 ± 11.0 Charlson-Deyo (mean, range) 0.66 (0 7)
Chief Complaints Symptom Description Questions Management Treatment Pain Treatment options Imaging follow-up Medication Non-pain symptoms General medical problems Limitations Etiology Prognosis Care coordination Injection follow-up Orthotics Imaging request Surgery Stimulator Disease course Recovery Test follow-up Therapy
Comments 29 comments in 292 responses All good or no comment = 12 Everything was great! All were nice & caring & took time to explain. Did great job n/a Pain removal = 7 Relieve pain to make me more active Pain meds & advice about my crunt (sp) condition
Comments? Questions about disease or procedure = 5 Keep me updated on my condition Answer questions about procedure - implant changes Constructive = 4 I like pictures--i understand and remember by visuals :) Stop these? For weekly appointments & clean bathrooms and tx area I waited 1 hr and 30 min to see doctor because check-in didn't check me in even though I was on time!
Preliminary Findings First 100 Patients overwhelmingly utilize the CST as a space to describe their symptoms, especially pain also used to note questions about their treatment options. Type of chief complaint does not depend on gender or medication history Description of pain is not dependent on medication history
Preliminary Findings Even patients with constructive feedback comments tend to check satisfied or leave unmarked opportunity for opened dialogue Rare negative events due to rescue process within clinic!
Hypothesis #3 Next Steps Association models of comments and complaints can be used to design POC interventions to help educate patients and enhance overall communication. Complete coding, modelling in progress Asher et al 2017: 12-month outcomes models based on QOD can be used to identify modifiable predictive factors for lumbar surgery
THANK YOU! Questions?
References 1. http://www.pcori.org/research-results/patient-centered-outcomes-research 2. http://thejns.org/doi/full/10.3171/2012.4.focus12106 3. https://www.ncbi.nlm.nih.gov/pubmed/18053372 4. https://www.ncbi.nlm.nih.gov/pubmed/27599908 5. https://www.ncbi.nlm.nih.gov/pubmed/27599908 6. https://www.ncbi.nlm.nih.gov/pubmed/27519824 7. http://www.encyclopedia.com/social-sciences/dictionaries-thesauruses-pictures-and-press-releases/grand-theory 8. http://www.analytictech.com/mb870/introtogt.htm 9. https://www.ncbi.nlm.nih.gov/pubmed/2945879 10. https://www.ncbi.nlm.nih.gov/pubmed/18053372 11. https://www.ncbi.nlm.nih.gov/pubmed/27658770 12. https://www.ncbi.nlm.nih.gov/pubmed/21051920 13. https://www.ncbi.nlm.nih.gov/pubmed/27399426 14. https://link.springer.com/article/10.1007/bf00988593 15. https://www.ncbi.nlm.nih.gov/pubmed/25498410 16. https://www.ncbi.nlm.nih.gov/pubmed/24005086 17. https://www.washingtonpost.com/national/health-science/i-won-the-doctor-lottery--but-only-after-some-badencounters/2017/05/26/de03222e-3be0-11e7-a058-ddbb23c75d82_story.html#comments 18. http://ww1.cpa-apc.org/publications/archives/cjp/2004/may/hasler.pdf 19. Gadalean, I, Cheptea, M, & Constantin, I (2011). Evaluation of patient satisfaction. Applied Medical Informatics, 29(4), 41-47.