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Implementation Science
Published in: Implementation Science 1/2017

Open Access 01-12-2017 | Methodology

Utilization of the Behavior Change Wheel framework to develop a model to improve cardiometabolic screening for people with severe mental illness

Authors: Christina Mangurian, Grace C. Niu, Dean Schillinger, John W. Newcomer, James Dilley, Margaret A. Handley

Published in: Implementation Science | Issue 1/2017

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Abstract

Background

Individuals with severe mental illness (e.g., schizophrenia, bipolar disorder) die 10–25 years earlier than the general population, primarily from premature cardiovascular disease (CVD). Contributing factors are complex, but include systemic-related factors of poorly integrated primary care and mental health services. Although evidence-based models exist for integrating mental health care into primary care settings, the evidence base for integrating medical care into specialty mental health settings is limited. Such models are referred to as “reverse” integration. In this paper, we describe the application of an implementation science framework in designing a model to improve CVD outcomes for individuals with severe mental illness (SMI) who receive services in a community mental health setting.

Methods

Using principles from the theory of planned behavior, focus groups were conducted to understand stakeholder perspectives of barriers to CVD risk factor screening and treatment identify potential target behaviors. We then applied results to the overarching Behavior Change Wheel framework, a systematic and theory-driven approach that incorporates the COM-B model (capability, opportunity, motivation, and behavior), to build an intervention to improve CVD risk factor screening and treatment for people with SMI.

Results

Following a stepped approach from the Behavior Change Wheel framework, a model to deliver primary preventive care for people that use community mental health settings as their de facto health home was developed. The CRANIUM (cardiometabolic risk assessment and treatment through a novel integration model for underserved populations with mental illness) model focuses on engaging community psychiatrists to expand their scope of practice to become responsible for CVD risk, with significant clinical decision support.

Conclusion

The CRANIUM model was designed by integrating behavioral change theory and implementation theory. CRANIUM is feasible to implement, is highly acceptable to, and targets provider behavior change, and is replicable and efficient for helping to integrate primary preventive care services in community mental health settings. CRANIUM can be scaled up to increase CVD preventive care delivery and ultimately improve health outcomes among people with SMI served within a public mental health care system.
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Literature
1.
Colton CW, Manderscheid RW. Congruencies in increased mortality rates, years of potential life lost, and causes of death among public mental health clients in eight states. Prev Chronic Dis. 2006;3(2):A42.PubMedPubMedCentral
2.
3.
Newcomer JW. Second-generation (atypical) antipsychotics and metabolic effects: a comprehensive literature review. CNS Drugs. 2005;19(Suppl 1):1–93.PubMed
4.
American Diabetes Association, American Psychiatric Association, American Association of Clinical Endocrinologists, North American Association for the Study of Obesity. Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care. 2004;27(2):596–601. https://​www.​ncbi.​nlm.​nih.​gov/​pubmed/​14747245.
5.
Giorda C, Picariello R, Nada E, Tartaglino B, Marafetti L, Costa G, et al. The impact of adherence to screening guidelines and of diabetes clinics referral on morbidity and mortality in diabetes. PLoS One. 2012;7(4):e33839.PubMedPubMedCentralCrossRef
6.
Mitchell A, Delaffon V, Vancampfort D, Correll C, De Hert M. Guideline concordant monitoring of metabolic risk in people treated with antipsychotic medication: systematic review and meta-analysis of screening practices. Psychol Med. 2012;42(01):125–47.PubMedCrossRef
7.
Burton A, Osborn D, Atkins L, Michie S, Gray B, Stevenson F, et al. Lowering cardiovascular disease risk for people with severe mental illnesses in primary care: a focus group study. PLoS One. 2015;10(8):e0136603.PubMedPubMedCentralCrossRef
8.
9.
10.
Kreyenbuhl J, Dixon LB, McCarthy JF, Soliman S, Ignacio RV, Valenstein M. Does adherence to medications for type 2 diabetes differ between individuals with vs without schizophrenia? Schizophr Bull. 2010;36(2):428–35. doi:10.​1093/​schbul/​sbn106.PubMedCrossRef
11.
Osborn D, Burton A, Walters K, Nazareth I, Heinkel S, Atkins L, et al. Evaluating the clinical and cost effectiveness of a behaviour change intervention for lowering cardiovascular disease risk for people with severe mental illnesses in primary care (PRIMROSE study): study protocol for a cluster randomised controlled trial. Trials. 2016;17(1):1.CrossRef
12.
13.
Murray CJ, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud C, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the global burden of disease study 2010. Lancet. 2012;380(9859):2197–223. doi:10.​1016/​S0140-6736(12)61689-4.PubMedCrossRef
14.
Katon WJ. Clinical and health services relationships between major depression, depressive symptoms, and general medical illness. Biol Psychiatry. 2003;54(3):216–26.PubMedCrossRef
15.
16.
Kessler RC, Berglund PA, Bruce ML, Koch JR, Laska EM, Leaf PJ, et al. The prevalence and correlates of untreated serious mental illness. Health Serv Res. 2001;36(6 Pt 1):987–1007.PubMedPubMedCentral
17.
18.
19.
Medicine Io. The National Academies Collection: reports funded by National Institutes of Health. Improving the quality of health care for mental and substance-use conditions: quality chasm series. Washington (DC): National Academies Press (US) National Academy of Sciences; 2006.
20.
21.
22.
Copeland LA, Zeber JE, Wang CP, Parchman ML, Lawrence VA, Valenstein M, et al. Patterns of primary care and mortality among patients with schizophrenia or diabetes: a cluster analysis approach to the retrospective study of healthcare utilization. BMC Health Serv Res. 2009;9:127. doi:10.​1186/​1472-6963-9-127.PubMedPubMedCentralCrossRef
23.
Druss BG, von Esenwein SA, Compton MT, Rask KJ, Zhao L, Parker RM. A randomized trial of medical care management for community mental health settings: the primary care access, referral, and evaluation (PCARE) study. Am J Psychiatry. 2010;167(2):151–9. doi:10.​1176/​appi.​ajp.​2009.​09050691.PubMedCrossRef
24.
Berren MR, Santiago JM, Zent MR, Carbone CP. Health care utilization by persons with severe and persistent mental illness. Psychiatr Serv. 1999;50(4):559–61.PubMedCrossRef
25.
26.
27.
Collins C, Hewson DL, Munger R, Wade T. Evolving models of behavioral health integration in primary care. New York: Milbank Memorial Fund; 2010.CrossRef
28.
29.
30.
Zung WW, Broadhead WE, Roth ME. Prevalence of depressive symptoms in primary care. J Fam Pract. 1993;37(4):337–44.PubMed
31.
Katon W, Von Korff M, Lin E, Lipscomb P, Russo J, Wagner E, et al. Distressed high utilizers of medical care. DSM-III-R diagnoses and treatment needs. Gen Hosp Psychiatry. 1990;12(6):355–62.PubMedCrossRef
32.
Agency for Health Care Policy and Research DGP. Depression in primary care: treatment of major depression. Rockville: U.S. Department of Health and Human Services; 1993.
33.
Pincus HA, Pettit AR. The societal costs of chronic major depression. J Clin Psychiatry. 2001;62(Suppl 6):5–9.PubMed
34.
McEvoy JP, Meyer JM, Goff DC, Nasrallah HA, Davis SM, Sullivan L, et al. Prevalence of the metabolic syndrome in patients with schizophrenia: baseline results from the clinical antipsychotic trials of intervention effectiveness (CATIE) schizophrenia trial and comparison with national estimates from NHANES III. Schizophr Res. 2005;80(1):19–32. doi:10.​1016/​j.​schres.​2005.​07.​014.PubMedCrossRef
35.
36.
James PA, Oparil S, Carter BL, et al. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the eighth joint national committee (jnc 8). JAMA. 2014;311(5):507–20. doi:10.​1001/​jama.​2013.​284427.PubMedCrossRef
37.
Stone NJ, Robinson JG, Lichtenstein AH, Merz CNB, Blum CB, Eckel RH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;63(25_PA):2889–934.PubMedCrossRef
38.
American Diabetes Association. Standards of medical care in diabetes-2016. Diabetes Care. 2016;39(Supplement 1):S1–S109.CrossRef
39.
40.
Hogan P, Dall T, Nikolov P. Economic costs of diabetes in the US in 2002. Diabetes Care. 2003;26(3):917–32.PubMedCrossRef
41.
42.
Thompson A, Hetrick SE, Álvarez-Jiménez M, Parker AG, Willet M, Hughes F, et al. Targeted intervention to improve monitoring of antipsychotic-induced weight gain and metabolic disturbance in first episode psychosis. Aust N Z J Psychiatry. 2011;45(9):740–8.PubMedCrossRef
43.
Velligan DI, Castillo D, Lopez L, Manaugh B, Davis C, Rodriguez J, et al. A case control study of the implementation of change model versus passive dissemination of practice guidelines for compliance in monitoring for metabolic syndrome. Community Ment Health J. 2013;49(2):141–9.PubMedCrossRef
44.
Kreyenbuhl J, Dixon LB, Brown CH, Medoff DR, Klingaman EA, Fang LJ, et al. A randomized controlled trial of a patient-centered approach to improve screening for the metabolic side effects of antipsychotic medications. Community Ment Health J. 2017;53(2):163–75. https://​www.​ncbi.​nlm.​nih.​gov/​pubmed/​27061185.
45.
Barnes T, Paton C, Hancock E, Cavanagh M, Taylor D, Lelliott P, on behalf of the UK Prescribing Observatory for Mental Health. Screening for the metabolic syndrome in community psychiatric patients prescribed antipsychotics: a quality improvement programme. Acta Psychiatr Scand. 2008;118(1):26–33.PubMedCrossRef
46.
47.
Scharf DM EN, Hackbarth NS, Horvitz-Lennon M, Beckman R, Han B, Lovejoy SL, Pincus HA, Burnam MA. Evaluation of the SAMHSA Primary and Behavioral Health Care Integration (PBHCI) Grant Program: final report (task 13) 2014.
48.
Bradford DW, Cunningham NT, Slubicki MN, McDuffie JR, Kilbourne AM, Nagi A, et al. An evidence synthesis of care models to improve general medical outcomes for individuals with serious mental illness: a systematic review. J Clin Psychiatry. 2013;74(8):e754–64.PubMedCrossRef
49.
Cabassa LJ, Stefancic A, O’Hara K, El-Bassel N, Lewis-Fernández R, Luchsinger JA, et al. Peer-led healthy lifestyle program in supportive housing: study protocol for a randomized controlled trial. Trials. 2015;16(1):1.CrossRef
50.
Cabassa LJ, Camacho D, Velez-Grau CM, Stefancic A. Peer-based health interventions for people with serious mental illness: a systematic literature review. J Psychiatr Res. 2016;84:80–9.PubMedCrossRef
51.
52.
DelMonte M, Bostwick J, Bess J, Dalack G. Evaluation of a computer-based intervention to enhance metabolic monitoring in psychiatry inpatients treated with second-generation antipsychotics. J Clin Pharm Ther. 2012;37(6):668–73.PubMedCrossRef
53.
Gilmer TP, O’Connor PJ, Sperl-Hillen JM, Rush WA, Johnson PE, Amundson GH, et al. Cost-effectiveness of an electronic medical record based clinical decision support system. Health Serv Res. 2012;47(6):2137–58.PubMedPubMedCentralCrossRef
54.
55.
Ramanuj PP. Improving blood and ECG monitoring among patients prescribed regular antipsychotic medications. Ment Health Fam Med. 2013;10(1):29.PubMedPubMedCentral
56.
Boulware LE, Daumit GL, Frick KD, Minkovitz CS, Lawrence RS, Powe NR. An evidence-based review of patient-centered behavioral interventions for hypertension. Am J Prev Med. 2001;21(3):221–32.PubMedCrossRef
57.
58.
Druss BG, von Esenwein SA, Glick GE, Deubler E, Lally C, Ward MC, et al. Randomized trial of an integrated behavioral health home: the health outcomes management and evaluation (HOME) study. Am J Psychiatr. 2016; doi:10.​1176/​appi.​ajp.​2016.​16050507.
59.
Alexander L, Druss B. Behavioral health homes for people with mental health and substance use conditions: the core clinical features. Washington: SAMHSA-HRSA Center for Integrated Health Solutions, US Department of Health and Human Services; 2012.
60.
Smith TE, Sederer LIA. New kind of homelessness for individuals with serious mental illness? The need for a “mental health home”. Psychiatr Serv. 2009;60(4):528–33.PubMedCrossRef
61.
62.
63.
64.
Cane J, O’Connor D, Michie S. Validation of the theoretical domains framework for use in behaviour change and implementation research. Implement Sci. 2012;7(1):37.PubMedPubMedCentralCrossRef
65.
Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179–211.CrossRef
66.
Godin G, Kok G. The theory of planned behavior: a review of its applications to health-related behaviors. Am J Health Promot. 1996;11(2):87–98.PubMedCrossRef
67.
68.
Colquhoun HL, Squires JE, Kolehmainen N, Fraser C, Grimshaw JM. Methods for designing interventions to change healthcare professionals’ behaviour: a systematic review. Implement Sci. 2017;12(1):30.PubMedPubMedCentralCrossRef
69.
Porcheret M, Main C, Croft P, McKinley R, Hassell A, Dziedzic K. Development of a behaviour change intervention: a case study on the practical application of theory. Implement Sci. 2014;9(1):42.PubMedPubMedCentralCrossRef
70.
French SD, Green SE, O’Connor DA, McKenzie JE, Francis JJ, Michie S, et al. Developing theory-informed behaviour change interventions to implement evidence into practice: a systematic approach using the theoretical domains framework. Implement Sci. 2012;7(1):38.PubMedPubMedCentralCrossRef
71.
Foy R, Francis JJ, Johnston M, Eccles M, Lecouturier J, Bamford C, et al. The development of a theory-based intervention to promote appropriate disclosure of a diagnosis of dementia. BMC Health Serv Res. 2007;7(1):207.PubMedPubMedCentralCrossRef
72.
Kolehmainen N, Francis JJ. Specifying content and mechanisms of change in interventions to change professionals’ practice: an illustration from the good goals study in occupational therapy. Implement Sci. 2012;7(1):100.PubMedPubMedCentralCrossRef
73.
Taylor N, Lawton R, Slater B, Foy R. The demonstration of a theory-based approach to the design of localized patient safety interventions. Implement Sci. 2013;8(1):123.PubMedPubMedCentralCrossRef
74.
Patey AM, Islam R, Francis JJ, Bryson GL, Grimshaw JM. Anesthesiologists’ and surgeons’ perceptions about routine pre-operative testing in low-risk patients: application of the Theoretical Domains Framework (TDF) to identify factors that influence physicians’ decisions to order pre-operative tests. Implement Sci. 2012;7(1):52.PubMedPubMedCentralCrossRef
75.
Squires JE, Suh KN, Linklater S, Bruce N, Gartke K, Graham ID, et al. Improving physician hand hygiene compliance using behavioural theories: a study protocol. Implement Sci. 2013;8(1):16.PubMedPubMedCentralCrossRef
76.
Liang L, Bernhardsson S, Vernooij RW, Armstrong MJ, Bussières A, Brouwers MC, et al. Use of theory to plan or evaluate guideline implementation among physicians: a scoping review. Implement Sci. 2017;12(1):26.PubMedPubMedCentralCrossRef
77.
Cabassa LJ, Druss B, Wang Y, Lewis-Fernández R. Collaborative planning approach to inform the implementation of a healthcare manager intervention for Hispanics with serious mental illness: a study protocol. Implement Sci. 2011;6(1):80.PubMedPubMedCentralCrossRef
78.
79.
Mangurian C, Modlin C, Williams L, Essock SM, Riano NS, Shumway M et al. A doctor is in the house: stakeholder focus groups about expanded scope of practice of community psychiatrists. Community Ment Health J. in press.
80.
81.
Morrato EH, Druss BG, Hartung DM, Valuck RJ, Thomas D, Allen R, et al. Small area variation and geographic and patient-specific determinants of metabolic testing in antipsychotic users. Pharmacoepidemiol Drug Saf. 2011;20(1):66–75. doi:10.​1002/​pds.​2062.PubMedCrossRef
82.
83.
84.
85.
Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness. JAMA. 2002;288(14):1775–9.PubMedCrossRef
86.
Rosenthal TC. The medical home: growing evidence to support a new approach to primary care. J Am Board Fam Med. 2008;21(5):427–40.PubMedCrossRef
87.
Bower P, Gilbody S. Stepped care in psychological therapies: access, effectiveness and efficiency. Br J Psychiatry. 2005;186(1):11–7.PubMedCrossRef
88.
Richardson WC, Berwick DM, Bisgard J, Bristow L, Buck C, Cassel C. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: Institute of Medicine, National Academy Press; 2001.
89.
Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;348:g1687.PubMedCrossRef
90.
Unutzer J, Katon W, Callahan CM, Williams JW Jr, Hunkeler E, Harpole L, et al. Collaborative care management of late-life depression in the primary care setting: a randomized controlled trial. JAMA. 2002;288(22):2836–45.PubMedCrossRef
91.
McAlpine DD, Mechanic D. Utilization of specialty mental health care among persons with severe mental illness: the roles of demographics, need, insurance, and risk. Health Serv Res. 2000;35(1 Pt 2):277.PubMedPubMedCentral
92.
93.
Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89(9):1322–7.PubMedPubMedCentralCrossRef
94.
Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4(1):50.PubMedPubMedCentralCrossRef
Metadata
Title
Utilization of the Behavior Change Wheel framework to develop a model to improve cardiometabolic screening for people with severe mental illness
Authors
Christina Mangurian
Grace C. Niu
Dean Schillinger
John W. Newcomer
James Dilley
Margaret A. Handley
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Implementation Science / Issue 1/2017
Electronic ISSN: 1748-5908
DOI
https://doi.org/10.1186/s13012-017-0663-z

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