Measuring patient engagement: development and psychometric properties of the Patient Health Engagement (PHE) Scale

Guendalina Graffigna, Serena Barello, Andrea Bonanomi, Edoardo Lozza, Guendalina Graffigna, Serena Barello, Andrea Bonanomi, Edoardo Lozza

Abstract

Beyond the rhetorical call for increasing patients' engagement, policy makers recognize the urgency to have an evidence-based measure of patients' engagement and capture its effect when planning and implementing initiatives aimed at sustaining the engagement of consumers in their health. In this paper, authors describe the Patient Health Engagement Scale (PHE-scale), a measure of patient engagement that is grounded in rigorous conceptualization and appropriate psychometric methods. The scale was developed based on our previous conceptualization of patient engagement (the PHE-model). In particular, the items of the PHE-scale were developed based on the findings from the literature review and from interviews with chronic patients. Initial psychometric analysis was performed to pilot test a preliminary version of the items. The items were then refined and administered to a national sample of chronic patients (N = 382) to assess the measure's psychometric performance. A final phase of test-retest reliability was performed. The analysis showed that the PHE Scale has good psychometric properties with good correlation with concurrent measures and solid reliability. Having a valid and reliable measure to assess patient engagement is the first step in understanding patient engagement and its role in health care quality, outcomes, and cost containment. The PHE Scale shows a promising clinical relevance, indicating that it can be used to tailor intervention and assess changes after patient engagement interventions.

Keywords: ordinal scale; patient activation; patient engagement; patient engagement measurement; patient health engagement scale; psychometric properties.

Figures

Figure 1
Figure 1
The patient health engagement model, adapted from Graffigna et al. (2013b).
Figure 2
Figure 2
CFA on PHE scale: Standardized estimates.

References

    1. Ahn Y. H., Yi C. H., Ham O. K., Kim B. J. (2014). Psychometric properties of the Korean version of the “Patient Activation Measure 13”(PAM13-K) in patients with osteoarthritis. Eval. Health Prof. 10.1177/0163278714540915[Epub ahead of print].
    1. Barello S., Graffigna G. (2014). Engaging patients to recover life projectuality: an Italian cross-disease framework. Qual. Life Res. 10.1007/s11136-014-0846-x[Epub ahead of print].
    1. Barello S., Graffigna G., Meyer C. E. (2015b). Ethics and Etiquette in Neonatal Intensive Care. A Comment on the value of parents' engagement in care, and recommendations for further advancing the field. JAMA Pediatr. 169, 190. 10.1001/jamapediatrics.2014.2958
    1. Barello S., Graffigna G., Savarese M., Bosio A. C. (2014a). Engaging patients in health management: towards a preliminary theoretical conceptualization. Psicologia Della Salute 3, 11–33 10.3280/PDS2014-003002
    1. Barello S., Graffigna G., Vegni E., Bosio A. C. (2014b). The challenges of conceptualizing patient engagement in healthcare: a lexicographic literature review. J. Particip. Med. 6:e9.
    1. Barello S., Graffigna G., Vegni E., Savarese M., Lombardi F., Bosio A. C. (2015a). Engage me in taking care of my heart”: a grounded theory study on patient-cardiologist relationship in the hospital management of heart failure. BMJ Open. (in press).
    1. Bellardita L., Graffigna G., Donegani S., Villani D., Villa S., Tresoldi V., et al. (2012). Patient's choice of observational strategy for early-stage prostate cancer. Neuropsycholol. Trends 12, 107–116 10.7358/neur-2012-012-bell
    1. Bonanomi A., Cantaluppi G., Nai Ruscone M., Osmetti S. A. (2014). A new estimator of Zumbo's Ordinal Alpha: a copula approach. Qual. Quant. 10.1007/s11135-014-0114-8
    1. Bonanomi A., Nai Ruscone M., Osmetti S. A. (2012). Reliability measurement for polytomous ordinal items: the empirical polychoric ordinal Alpha. Quad. Statist. 14, 53–56.
    1. Brenk-Franz K., Hibbard J. H., Herrmann W. J., Freund T., Szecsenyi J., Djalali S., et al. . (2013). Validation of the German version of the patient activation measure 13 (PAM13-D) in an international multicentre study of primary care patients. PLoS ONE 8:e74786. 10.1371/journal.pone.0074786
    1. Burns K. K., Bellows M., Eigenseher C., Jackson K., Gallivan J., Rees J. (2014). Exploring patient engagement practices and resources within a health care system: applying a multi-phased mixed methods knowledge mobilization approach. Int. J. Mult. Res. Approach 8, 233–247 10.1080/18340806.2014.11082063
    1. Clancy C. M. (2011). Patient engagement in health care. Health Serv. Res. 46, 389–393. 10.1111/j.1475-6773.2011.01254.x
    1. Coulter A. (2012a). Patient engagement—what works? J. Ambul. Care Manage. 35, 80–89. 10.1097/JAC.0b013e318249e0fd
    1. Coulter A. (2012b). Leadership for Patient Engagement. London: The King's Fund.
    1. Coulter A., Safran D., Wasson J. H. (2012). On the language and content of patient engagement. J. Ambl. Care Manage. 35, 78–79. 10.1097/JAC.0b013e31824a5676
    1. Crawford M. J., Rutter D., Manley C., Weaver T., Bhui K., Fulop N., et al. . (2002). Systematic review of involving patients in the planning and development of health care. BMJ 325:1263. 10.1136/bmj.325.7375.1263
    1. Davis K., Schoenbaum S. C., Audet A. M. (2005). A 2020 vision of patient−centered primary care. J. Gen. Int. Med. 20, 953–957. 10.1111/j.1525-1497.2005.0178.x
    1. Fabbrini G., Abbruzzese G., Barone P., Antonini A., Tinazzi M., Castegnaro G., et al. . (2013). Adherence to anti-Parkinson drug therapy in the “REASON” sample of Italian patients with Parkinson's disease: the linguistic validation of the Italian version of the “Morisky Medical Adherence scale-4 items. Neurol. Sci. 34, 2015–2022. 10.1007/s10072-013-1438-1
    1. Fleiss J. (1986). The Design and Analysis of Clinical Experiments. New York, NY: John Wiley and Sons.
    1. Furnham A. (1986). Response bias, social desirability and dissimulation. Pers. Individ. Dif. 7, 385–400. 10.1016/0191-8869(86)90014-0
    1. Graffigna G., Barello S., Libreri C., Bosio C. A. (2014). How to engage type-2 diabetic patients in their own health management: implications for clinical practice. BMC Public Health 14:648. 10.1186/1471-2458-14-648
    1. Graffigna G., Barello S., Riva G. (2013a). Technologies for patient engagement. Health Aff. 32, 1172–1172. 10.1377/hlthaff.2013.0279
    1. Graffigna G., Barello S., Riva G. (2013c). How to make health information technology effective? The challenge of patient engagement. Arch. Phys. Med. Rehabil. 94, 2034–2035. 10.1016/j.apmr.2013.04.024
    1. Graffigna G., Barello S., Triberti S. (2015). Patient Engagement: A Consumer-Centered Model to Innovate Healthcare. Berlin: DeGruyter Open.
    1. Graffigna G., Barello S., Wiederhold B. K., Bosio A. C., Riva G. (2013b). Positive technology as a driver for health engagement. Ann. Rev. Cyberther. Telemed. 9, 9–17. 10.3233/978-1-61499-282-0-9
    1. Greene J., Hibbard J. H. (2012). Why does patient activation matter? An examination of the relationships between patient activation and health-related outcomes. J. Gen. Int. Med. 27, 520–526. 10.1007/s11606-011-1931-2
    1. Hardyman W., Daunt K. L., Kitchener M. (2015). Value co-creation through patient engagement in health care: a micro-level approach and research agenda. Public Manag. Rev. 17, 90–107 10.1080/14719037.2014.881539
    1. Hartholt K. A., van Beeck E. F., Polinder S., van der Velde N., van Lieshout E. M., Panneman M. J., et al. . (2011). Societal consequences of falls in the older population: injuries, healthcare costs, and long-term reduced quality of life. J. Trauma 71, 748–753. 10.1097/TA.0b013e3181f6f5e5
    1. Hibbard J. H., Mahoney E. (2010). Toward a theory of patient and consumer activation. Patient Educ. Couns. 78, 377–381. 10.1016/j.pec.2009.12.015
    1. Hibbard J. H., Mahoney E. R., Stockard J., Tusler M. (2005). Development and testing of a short form of the patient activation measure. Health Serv. Res. 40, 1918–1930. 10.1111/j.1475-6773.2005.00438.x
    1. Hibbard J. H., Stockard J., Mahoney E. R., Tusler M. (2004). Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers. Health Serv. Res. 39, 1005–1026. 10.1111/j.1475-6773.2004.00269.x
    1. Hor S., Godbold N., Collier A., Iedema I. (2013). Finding the Patient in Safety. Health 17, 567–583. 10.1177/1363459312472082
    1. Lamiani G., Barello S., Browning D. M., Vegni E., Meyer E. C. (2012). Uncovering and validating clinicians' experiential knowledge when facing difficult conversations: a cross-cultural perspective. Patient Educ. Couns. 87, 307–312. 10.1016/j.pec.2011.11.012
    1. Lassman D., Hartman M., Washington B., Andrews K., Catlin A. (2014). US health spending trends by age and gender: selected years 2002–10. Health Aff. 33, 815–822. 10.1377/hlthaff.2013.1224
    1. Magnezi R., Glasser S. (2014). Psychometric properties of the hebrew translation of the patient activation measure (PAM-13). PLoS ONE 9:e113391. 10.1371/journal.pone.0113391
    1. Maindal H. T., Sokolowski I., Vedsted P. (2009). Translation, adaptation and validation of the American short form Patient Activation Measure (PAM13) in a Danish version. BMC Public Health 9:209. 10.1186/1471-2458-9-209
    1. Menichetti J., Libreri C., Lozza E., Graffigna G. (2014). Giving patients a starring role in their own care: a bibliometric analysis of the on-going literature debate. Health Expect. 10.1111/hex.12299[Epub ahead of print].
    1. Morisky D. E., Ang A., Krousel-Wood M., Ward H. J. (2008). Predictive validity of a medication adherence measure in an outpatient setting. J. Clin. Hypertens. 10, 348–354. 10.1111/j.1751-7176.2008.07572.x
    1. Morisky D. E., Green L. W., Levine D. M. (1986). Concurrent and predictive validity of a self-reported measure of medication adherence. Med. Care 24, 67–74. 10.1097/00005650-198601000-00007
    1. Ocloo J. E., Fulop N. J. (2012). Developing a ‘Critical’ approach to patient and public involvement in patient safety in the NHS: learning lessons from other parts of the public sector? Health Expect. 15, 424–432. 10.1111/j.1369-7625.2011.00695.x
    1. Pallin D. J., Espinola J. A., Camargo C. A. (2014). US population aging and demand for inpatient services. J. Hospit. Med. 9, 193–196. 10.1002/jhm.2145
    1. Pearson K. (1900). Mathematical contribution to the theory of evolution. Philos. Trans. R. Soc. London Ser. A 195, 1–47.
    1. Provenzi L., Borgatti R., Menozzi G., Montirosso R. (2015). A dynamic system analysis of dyadic flexibility and stability across the Face-to-Face Still-Face procedure: application of the State Space Grid. Infant Behav. Dev. 38, 1–10. 10.1016/j.infbeh.2014.10.001
    1. Renedo A., Marston C. (2011). Healthcare Professionals' representations of ‘patient and public involvement’ and creation of ‘public participant’ identities: implications for the development of inclusive and bottom-up community participation initiatives. J. Com. Appl. Soc. Psych. 21, 268–280 10.1002/casp.1092
    1. Shalansky S. J., Levy A. R., Ignaszewski A. P. (2004). Self-reported Morisky score for identifying nonadherence with cardiovascular medications. Ann. Pharmacother. 38, 1363–1368. 10.1345/aph.1E071
    1. Spatola C. A., Manzoni G. M., Castelnuovo G., Malfatto G., Facchini M., Goodwin C. L., et al. . (2014). The ACTonHEART study: rationale and design of a randomized controlled clinical trial comparing a brief intervention based on Acceptance and Commitment Therapy to usual secondary prevention care of coronary heart disease. Health Qual. Life Outcomes 12, 1–10. 10.1186/1477-7525-12-22
    1. Staniszewska S., Herron-Marx S., Mockford C. (2008). Measuring the impact of patient and public involvement: the need for an evidence base. Int. J. Qual. Health Care 20, 373–374. 10.1093/intqhc/mzn044
    1. Steinmann L., Telser H., Zweifel P. S. (2007). Aging and future healthcare expenditure: a consistent approach. Forum Health Econ. Policy 10, 1–26 10.2202/1558-9544.1041
    1. Wright B. D., Linacre J. M., Gustafson J. E., Martin-Lof P. (1994). Reasonable mean-square fit values. Rasch Meas. Trans. 8, 370.
    1. Zill J. M., Dwinger S., Kriston L., Rohenkohl A., Härter M., Dirmaier J. (2013). Psychometric evaluation of the German version of the patient activation measure (PAM13). BMC Public Health 13:1027. 10.1186/1471-2458-13-1027
    1. Zumbo B. D., Gadermann A. M., Zeisser C. (2007). Ordinal versions of coefficient Alpha and Theta for Likert rating scales. J. Mod. Appl. Stat. Methods 6, 21–29.

Source: PubMed

3
Abonneren