Advertisement
Original research| Volume 100, ISSUE 6, P1032-1041, June 2019

Inpatient Rehabilitation Quality of Care From the Patient’s Perspective: Effect of Data Collection Timing and Patient Characteristics

Published:November 23, 2018DOI:https://doi.org/10.1016/j.apmr.2018.10.019

      Abstract

      Objective

      To compare, by collection time and patient characteristics, inpatient rehabilitation quality measure scores calculated using patient-reported data.

      Design

      Cohort study of rehabilitation inpatients with neurologic conditions who reported their experience of care and pain status at discharge and 1month after discharge.

      Setting

      Two inpatient rehabilitation facilities (IRFs).

      Participants

      Patients with neurologic conditions (N=391).

      Interventions

      Not applicable.

      Main Outcome Measures

      We calculated 18 quality measure scores using participants’ responses to 55 experience of care and health status questions addressing communication, support and encouragement, care coordination, discharge information, goals, new medications, responsiveness of staff, cleanliness, quietness, pain management, care transitions, overall hospital rating, willingness to recommend, and pain.

      Results

      Of the 391 participants reporting at discharge, 277 (71%) also reported postdischarge after multiple attempts by e-mail, mail, and telephone. Discharge experience of care quality scores ranged from 25% (responsiveness of hospital staff) to 75% (willingness to recommend hospital); corresponding postdischarge scores were 32% to 87%, respectively. Five of the 16 experience of care quality scores increased significantly between discharge and postdischarge. The percentage of participants reporting high pain levels at discharge did not change across time periods. Patients with less education, older age, higher motor and cognitive function, and those who were not Hispanic or black had more favorable quality measure scores.

      Conclusion

      Patients’ experience of care responses tended to be more favorable after discharge compared to discharge, suggesting that survey timing is important. Responses were more favorable for patients with selected characteristics, suggesting the possible need for risk adjustment if patient-reported quality measure scores are compared across IRFs.

      Keywords

      List of abbreviations:

      CTM (Care Transitions Measure), HCAHPS (Hospital Consumer Assessment of Healthcare Provider Systems), ICC (intraclass correlation coefficient), IRF (inpatient rehabilitation facility), MDS (Minimum Data Set), PCT (patient care technician), PREM (patient-reported experience measure), PROM (patient-reported outcome measure), PROMIS (Patient Reported Outcome Measures Information System)
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Archives of Physical Medicine and Rehabilitation
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Committee on Quality Health Care in America and Institute of Medicine
        Crossing the quality chasm: a new heath system for the 21st century.
        National Academies Press, Washington (DC)2001
        • National Quality Forum
        Priority setting for healthcare performance: Addressing performance measure gaps person-centered care and outcomes.
        National Quality Forum, August 15, 2014 (Available at:)
        • Snyder C.
        • Brundage M.
        Integrating patient-reported outcomes in healthcare policy, research and practice.
        Expert Rev Pharmacoecon Outcomes Res. 2010; 10: 351-353
        • Centers for Medicare and Medicaid Services
        IRF quality reporting program measures information.
        (Available at:)
        • Burroughs T.E.
        • Waterman B.M.
        • Gilin D.
        • Adams D.
        • McCollegan J.
        • Cira J.
        Do on-site patient satisfaction surveys bias results?.
        Jt Comm J Qual Patient Saf. 2005; 31: 158-166
        • Saal D.
        • Nuebling M.
        • Husemann Y.
        • Heidegger T.
        Effect of timing on the response to postal questionnaires concerning satisfaction with anaesthesia care.
        Br J Anaesth. 2005; 94: 206-210
        • Lin O.S.
        • Schembre D.B.
        • Ayub K.
        • et al.
        Patient satisfaction scores for endoscopic procedures: impact of a survey-collection method.
        Gastrointest Endosc. 2007; 65: 775-781
        • Stevens M.
        • Reininga I.H.
        • Boss N.A.
        • van Horn J.R.
        Patient satisfaction at and after discharge. Effect of a time lag.
        Patient Educ Couns. 2006; 60: 241-245
        • Bendall-Lyon D.
        • Powers T.L.
        • Swan J.E.
        Time does not heal all wounds. Patients report lower satisfaction levels as time goes by.
        Mark Health Serv. 2001; 21: 10-14
        • Wongus R.
        • Schluterman N.H.
        • Feinstein S.
        • McGirt N.
        • Greenberg D.R.
        • Schwartz D.B.
        Patient satisfaction reported by in-visit and after-visit surveys.
        PXJ. 2015; 2: 68-74
        • Jackson J.L.
        • Chamberlin J.
        • Kroenke K.
        Predictors of patient satisfaction.
        Soc Sci Med. 2001; 52: 609-620
        • Broderick J.E.
        • Schwartz J.E.
        • Vikingstad G.
        • Pribbernow M.
        • Grossman S.
        • Stone A.A.
        The accuracy of pain and fatigue items across different reporting periods.
        Pain. 2008; 139: 146-157
        • Zaslavsky A.M.
        • Zaborski L.
        • Cleary P.D.
        Does the effect of respondent characteristics on consumer assessments vary across health plans?.
        Med Care Res Rev. 2000; 57: 379-394
        • O'Malley A.J.
        • Zaslavsky A.M.
        • Elliott M.N.
        • Zaborski L.
        • Cleary P.D.
        Case-mix adjustment of the CAHPS Hospital Survey.
        Health Serv Res. 2005; 40: 2162-2181
        • Elliott M.N.
        • Swartz R.
        • Adams J.
        • Spritzer K.L.
        • Hays R.D.
        Case-mix adjustment of the National CAHPS benchmarking data 1.0: a violation of model assumptions?.
        Health Serv Res. 2001; 36: 555-573
        • Bjertnaes O.A.
        • Sjetne I.S.
        • Iversen H.H.
        Overall patient satisfaction with hospitals: effects of patient-reported experiences and fulfilment of expectations.
        BMJ Quality Saf. 2012; 21: 39-46
        • Franchignoni F.
        • Ottonello M.
        • Benevolo E.
        • Tesio L.
        Satisfaction with hospital rehabilitation: is it related to life satisfaction, functional status, age or education?.
        J Rehabil Med. 2002; 34: 105-108
        • Heinemann A.W.
        • Deutsch A.
        • Cella D.
        • et al.
        Feasibility of collecting patient-reported outcomes for inpatient rehabilitation quality reporting.
        Health Serv Res. 2018; 53: 1834-1850
        • Centers for Medicare and Medicaid Services
        HCAHPS three-state pilot study analysis results.
        (Available at:) (Accessed August 20, 2017)
        • Elliott M.N.
        • Zaslavsky A.M.
        • Goldstein E.
        • et al.
        Effects of survey mode, patient mix, and nonresponse on CAHPS hospital survey scores.
        Health Serv Res. 2009; 44: 501-518
        • Coleman E.A.
        • Mahoney E.
        • Parry C.
        Assessing the quality of preparation for posthospital care from the patient's perspective: the care transitions measure.
        Med Care. 2005; 43: 246-255
        • Parry C.
        • Mahoney E.
        • Chalmers S.A.
        • Coleman E.A.
        Assessing the quality of transitional care: further applications of the care transitions measure.
        Med Care. 2008; 46: 317-322
        • Saliba D.
        • Buchanan J.
        Making the investment count: revision of the Minimum Data Set for nursing homes, MDS 3.0.
        J Am Med Dir Assoc. 2012; 13: 602-610
        • Saliba D.
        • Buchanan J.
        Development and Validation of Revised Nursing Home Assessment Tool: MDS 3.0.
        (Available at:) (Accessed August 20, 2017)
        • Amtmann D.
        • Cook K.F.
        • Jensen M.P.
        • et al.
        Development of a PROMIS item bank to measure pain interference.
        Pain. 2010; 150: 173-182
        • Kim J.
        • Chung H.
        • Amtmann D.
        • Revicki D.A.
        • Cook K.F.
        Measurement invariance of the PROMIS pain interference item bank across community and clinical samples.
        Qual Life Res. 2013; 22: 501-507
        • National Quality Forum
        Composite measure submission form.
        (Available at:)
        • McGory M.
        • Shekelle P.G.
        • Ko C.
        Development of quality indicators for patients undergoing colorectal cancer surgery.
        J Natl Cancer Inst. 2006; 98: 1623-1633
        • Rothman K.J.
        No adjustments are needed for multiple comparisons.
        Epidemiology. 1990; 1: 43-46
        • Saville D.J.
        Multiple comparison procedures: the practical solution.
        Am Stat. 1990; 44: 147-180
      1. Centers for Medicare and Medicaid Services. Hospital compare. Medicare.gov. Available at: https://www.medicare.gov/hospitalcompare/Data/Data-Updated.html#%20. Accessed July 4, 2018.

        • Gans B.M.
        Evolving models of rehabilitation-related patient safety and quality: PIECES.
        Arch Phys Med Rehabil. 2018; 99: 1033-1034
        • Okun S.
        • Schoenbaum S.
        • Andrews D.
        • et al.
        Patients and health care teams forging effective partnerships.
        Institute of Medicine, Washington, DC2014
        • Strasser D.C.
        • Burridge A.B.
        • Falconer J.A.
        • Uomoto J.M.
        • Herrin J.
        Toward spanning the quality chasm: an examination of team functioning measures.
        Arch Phys Med Rehabil. 2014; 95: 2220-2223
        • Brown M.
        • Levack W.
        • McPherson K.M.
        • et al.
        Survival, momentum, and things that make me “me”: patients’ perceptions of goal setting after stroke.
        Disabil Rehabil. 2014; 36: 1020-1026
        • Lexell E.M.
        • Lexell J.
        • Larsson-Lund M.
        The rehabilitation plan can support clients’ active engagement and facilitate the process of change – experiences from people with late effects of polio participating in a rehabilitation programme.
        Disabil Rehabil. 2016; 38: 329-336
        • Dossa A.
        • Bokhour B.
        • Hoenig H.
        Care transitions from the hospital to home for patients with mobility impairments: patient and family caregiver experiences.
        Rehabil Nurs. 2012; 37: 277-285
        • Elliott M.N.
        • Lehrman W.G.
        • Goldstein E.H.
        • et al.
        Hospital survey shows improvements in patient experience.
        Health Aff (Millwood). 2010; 29: 2061-2067
        • Giordano L.A.
        • Elliott M.N.
        • Goldstein E.
        • Lehrman W.G.
        • Spencer P.A.
        Development, implementation, and public reporting of the HCAHPS survey.
        Med Care Res Rev. 2010; 67: 27-37
        • Goldstein E.
        • Farquhar M.
        • Crofton C.
        • Darby C.
        • Garfinkel S.
        Measuring hospital care from the patients' perspective: an overview of the CAHPS Hospital Survey development process.
        Health Serv Res. 2005; 40: 1977-1995
        • Nolan T.
        • Berwick D.M.
        All-or-none measurement raises the bar on performance.
        JAMA. 2006; 295: 1168-1170
        • Elliott M.N.
        • Haviland A.M.
        • Kanouse D.E.
        • Hambarsoomian K.
        • Hays R.D.
        Adjusting for subgroup differences in extreme response tendency in ratings of health care: impact on disparity estimates.
        Health Serv Res. 2009; 44: 542-561