Design, implementation and evaluation of PSY-KOMO care - Improving the quality of treatment for people with severe mental illness to reduce physical comorbidity and prevent increased mortality: a study protocol

Design, implementation and evaluation of PSY-KOMO care - Improving the quality of treatment for people with severe mental illness to reduce physical comorbidity and prevent increased mortality: a study protocol | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Design, implementation and evaluation of PSY-KOMO care - Improving the quality of treatment for people with severe mental illness to reduce physical comorbidity and prevent increased mortality: a study protocol Anja Viehmann, Natalia Wege, Verena Leve, Frank Jacobi, Martina Hahn, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9488151/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Individuals with severe mental illness (SMI) have an increased risk for physical comorbidities, such as diabetes and cardiovascular disease, leading to reduced life expectancy. The overshadowing phenomenon is a major contributor to this health inequality, as clinical attention is predominantly focused on the management of psychiatric conditions, often to the detriment of physical health problems. PSY-KOMO aims at filling this gap by implementing an intervention focused on improving the prevention, detection and management of physical diseases in SMI patients through structuring the diagnostic approach of psychiatrists, providing patient navigators and building interdisciplinary health networks. Methods: The study design is a multicentre, non-randomized study with an intervention group (IG) receiving the new treatment PSY-KOMO care compared with a matched external control group (CG) (quasi-experimental design). Three endpoints are evaluated: (1) Improvement in the detection of physical diseases (incidence); (2) improvement in guideline-based treatment of the physical diseases; and (3) improvement of prevention and screening for physical diseases. These endpoints are compared between the IG and the external CG using regression analyses. Based on the sample size calculation, 1,302 participants with severe mental illness (SMI) were planned to be recruited for the intervention group (IG) to analyse the primary endpoint. Patients were included from four distinct regions in Germany: Frankfurt am Main, Neuss, Greifswald, and Göppingen. For analyses and matching of an external control group, data from the Association of Statutory Health Insurance Physicians are used. Discussion: The results will be used to evaluate the effectiveness of the PSY-KOMO intervention. Trial registration: DRKS (DRKS - Deutsches Register Klinischer Studien)- Deutsches Register Klinischer Studien, DRKS00030200 registered on 27 th January 2023. Psychiatry Epidemiology PSY-KOMO study protocol intervention study severe mental illness physical comorbidity quality of treatment patient navigator Background Despite significant improvements in health services and treatments, individuals with severe mental illness (SMI), including schizophrenia, bipolar disorder, and major depressive disorder, continue to exhibit substantially higher morbidity rates compared to the general population (Saha et al, 2013; Laursen et al, 2013, 2014; Chesney et al, 2014; Walker et al, 2015; Hjorthøj et al, 2017; Lee et al, 2018). Remarkably, the predominant cause of mortality among those with SMI is attributed to physical conditions such as cardiovascular diseases (Correll et al, 2022; Laursen et al, 2014) and diabetes (Vancampfort et al, 2016), which are notably prevalent among SMI patients. A comprehensive meta-analysis conducted by Walker et al (2015) explored the high risk of premature mortality in individuals with SMI, reported cardiovascular diseases as a leading cause of death. According to their findings, 67.3% of deaths arise from natural causes and 17.5% from unnatural causes such as suicide (15.2% other/unkown) (Walker et al, 2015). Another meta-analysis (Hjorthøj et al, 2017) reports that people with SMI have a 2-fold increased risk of all-cause mortality and a 3.5-fold increased risk of death from cardiovascular disease, with a 10–20 years reduction in life expectancy compared to the general population. In addition, research has highlighted an increased risk of cancer mortality among SMI patients. While these groups do not have a higher incidence of many types of cancer compared to the general population, their cancer mortality rates are significantly higher, mostly due to delayed detection, screening inequalities and poor compliance with treatment (Kunkel et al, 1997; Kisely et al, 2008; Howard et al, 2010). Our own research group analysed physical comorbidity and excess mortality for the German SMI population for the first time (including borderline personality disorder; Schneider et al, 2019). The excess of morbidity and premature death in SMI patients involves a complex interplay of various factors. Research indicates that individuals with severe mental illness (SMI) are predisposed to unhealthy lifestyle choices, including prevalent smoking habits (Lasser et al, 2000; Ziedonis et al, 2003; Prochaska et al, 2011), sedentary lifestyle (Rethorst et al, 2017; Peeling et al, 2019) and dietary patterns with higher consumption of saturated fat and refined sugars (Teasdale et al, 2019; Costa et al, 2019). These factors increase the risk of developing obesity and the metabolic syndrome and its associated health consequences (e.g. cardiovascular disease, stroke, type 2 diabetes). Studies have shown that people with SMI are more likely to be overweight or obese than the general population (McElroy et al, 2004; Simon et al, 2006; McIntyre et al, 2019). Importantly, this is partly due to the side effects of antipsychotics, which can include weight gain, insulin resistance and dyslipidaemia. Moreover, individuals with SMI face considerable barriers in accessing healthcare (Krausz et al, 2003; De Hert et al, 2011), which can exacerbate existing health problems. Adherence to treatment remains a challenge, caused by limited understanding of the illness, concerns about potential side effects, the stigma of mental illness, and practical barriers that complicate the process of accessing appropriate medical treatment (Kohn et al, 2022). In addition, SMI patients received suboptimal care in terms of revascularisation, secondary prevention, including the prescription of statins, beta-blockers and antiplatelets, and follow-up compared with patients without a psychiatric diagnosis (Mitchell & Lord 2010). Furthermore, the symptomatology of severe mental illness and stigma may limit patients' access to quality medical care and impair communication with health professionals. According to current research, improving access and provision of healthcare for individuals with SMI is an important issue. In addition, the development of evidence-based clinical guidelines is needed to facilitate the scale-up of care for physical health conditions and their risk factors in this vulnerable group (Thornicroft et al, 2018). To close this gap in the health care services utilisation in individuals with SMI, it is essential to shift the focus towards promoting the use of existing healthcare resources and the referral of those with SMI to health care resources (Woltmann et al, 2012). Yet, there remains a lack of evaluation studies documenting the effectiveness of such interventions. The interventions mostly consisted of individual support, particularly care-management and self-management strategies, with group formats sometimes being added as a supplementary element. To address the physical health-related deficiencies of this population, more complex and multifactorial interventions that incorporate elements, such as coordination with community resources, continuous interaction with service users and health care providers, and the provision of person-centred care, appear to be promising (Firth et al, 2019; Strunz et al, 2022; Richardson et al, 2020; McGinty et al, 2015). This is where the PSY-KOMO care initiative comes into action. Therefore, the project objectives are, to implement and evaluate the effectiveness of the PSY-KOMO care model, aiming at improving physical health outcomes among SMI patients through a structured program involving patient navigators and local interdisciplinary health networks. Methods In order to describe PSY-KOMO we follow the “Standards for Reporting Implementation Studies Statement” (StaRI) (Pinnock et al, 2017). Trial Design The impact evaluation of the PSY-KOMO intervention is conducted as a multicentre non-randomized longitudinal study with a matched external control group. The primary analysis utilized secondary data from the Association of Statutory Health Insurance Physicians (ASHIP). The evaluation is being performed by an independent evaluation agency. Participants The PSY-KOMO care model was implemented in four regions in Germany, which differed in terms of settlement geography (rural, urban, mid-urban), population composition, and coverage with medical care: Frankfurt/Main, Göppingen, Greifswald, and Neuss. These sites were also spatially distributed across Germany. Recruitment took place on two levels. Several healthcare institutions in a defined geographical region, such as psychiatrists in private practice) and outpatient units of psychiatric hospitals and university departments of psychiatry, respectively, were asked to participate in PSY-KOMO care and in the evaluation study. Through a study-specific training, it was ensured that the participating physicians were familiar with the PSY-KOMO care model and the study procedures, such as inclusion criteria (age ≥ 18, confirmed ICD-10 diagnosis of SMI (ICD 10-Codes: F20.x, F21.x, F22.x, F25.x, F30.x, F31.x, F32.2, F32.3, F33.2, F33.3, F60.3x), adequate language skills in German, membership in a statutory health insurance, informed consent for study participation) and exclusion criteria (relevant cognitive limitation, advanced dementia), data collection procedures, and data protection. Patients of participating psychiatrists were approached in their practices or psychiatric outpatient departments, informed, and asked to participate. Any person who met the inclusion criteria could be asked to participate in the study, regardless of their physical health status. Subjects who signed the informed consent where then either directly screened or received an appointment to undergo the screening. Control group A multivariate matching technique based on data from the ASHIP was employed to establish the external control group. The matching pool consisted of patients who met the same inclusion criteria but were treated in neighbouring regions to prevent spill-over effects. The 1:1 Nearest Neighbor matching utilized various matching variables including demographic characteristics, health status indicators (particularly physical comorbidities), and healthcare utilization patterns (both psychiatric and general medical services). The procedure combined exact matching (primarily for inclusion criteria) with caliper matching approaches. Matching algorithms was based on Mahalanobis distance calculations. The target estimand of this procedure was the Average Treatment Effect on the Treated (ATT). The balance between intervention and control group was evaluated using standardized mean differences or differences in frequency distributions. Description of the PSY-KOMO intervention The aim of the new form of care “PSY-KOMO” is to improve the detection of physical diseases in SMI, to achieve a stronger orientation of their treatment towards guidelines, and to increase the use of preventive screening. PSY-KOMO intervention consists of several modules and is designed as an individual intervention. Within the evaluation study, the duration of the intervention was about six months from the day of inclusion and a screening for physical diseases. PSY-KOMO Modules The new PSY-KOMO care program has a modular structure. Stage 1 must be completed by every person participating in PSY-KOMO, while elements from Stage 2 can be utilized as needed. Stage 1 – Screening Trained, certified psychiatrists carry out a standardized screening for all patients after inclusion of the participants of the PSY-KOMO study. This takes place regardless of whether there are any particular risks, pre-existing conditions, expected ADRs or secondary conditions. The screening is carried out once at the beginning and represents structured, standardized history taking, medical examinations (measurement of blood pressure and weight) and documentation of prescribed medication with the help of a documentation sheet. Stage 2 – Patient Education/Prevention Even with unremarkable somatic findings, there is an increased risk of an additional somatic illness due to the existing severe mental illness and potentially due to lifestyle. Therefore, all interested patients are referred to locally available prevention and training measures and to standard care services, such as exercise training, smoking cessation, nutritional counselling, and vaccinations. Online modules, for example on nutrition and exercise, are offered to all patients due to their general informational nature; a target-group-specific website ( www.psy-komo-tut-mir-gut.de ) in simple language was developed for this purpose. Further medical measures If there is suspicion of one or more somatic illnesses appearing to be untreated or inadequately treated, patients are referred by their psychiatrists to a general practitioner or specialist for general medical diagnostics and, if necessary, treatment as part of standard care. On request, patients are supported by patient navigators in accessing further examinations and care services, either during the consultation or through a local information sheet. Patient Navigators Module Patient navigators are introduced to support the adequate utilisation of prevention and care services, and to promote patient motivation and adherence. These guides are healthcare professionals, particularly nurses and medical assistants, who have been trained and certified for this project. Their role is to support patients through the healthcare system for a period of six months (the intervention phase), providing assistance as required and reducing barriers to accessing prevention and care services through individually tailored measures. Each patient navigator has worked at one of the four study sites. Telephone Consultation Module for Pharmacotherapy and ADR Risk Minimization A specific medical telephone consultation service offered by LVR-Klinikum Düsseldorf provides participating practitioners with advice on prescribing psychotropic and medication (including polypharmacy), adverse drug reactions (ADRs) and interactions, particularly those involving general medical and psychotropic substances. This is carried out in close collaboration with an interaction detection system established at the German Federal Institute for Drugs and Medical Devices (BfArM). Frequent and impactful ADRs and interactions are addressed in educational material (leaflets) and made available to care providers throughout the project. Regions, Certified Physicians, and Practice Networks At the four regional study centers, medical project staff (specialists in psychiatry) were available to the certified physicians to coordinate and support patient-centred care with the participating physicians and patient navigators. Primary and secondary outcomes and hypotheses The primary outcome is the initial diagnosis of somatic diseases (disease detection; from 10 internal medical diagnoses, see below). Further outcomes are 2) treatment of somatic diseases according to guidelines and 3) utilization of preventive and early detection services. The three hypotheses of the effectiveness evaluations target the three areas detection, treatment and prevention. Compared to the control group… H1: the intervention is associated with higher detection and diagnostic clarification of existing somatic diseases that were previously undiagnosed (improvement in disease detection). H2: the intervention is associated with a higher proportion of both already known somatic diseases and somatic diseases diagnosed for the first time during the observation period being treated according to the German guidelines for the respective diseases (improvement in guideline-based treatment). H3: the intervention is associated with an increased proportion of participants utilizing preventive and early detection services. In addition, longitudinal changes in life style factors should be examined, expecting a positive effect of PSY-KOMO on change in physical activity, smoking behaviour and alcohol consumption. Data basis and analysis periods ASHIP data, including pharmacy billing records, has been utilized for analyzing the three study hypotheses. The data have been transmitted through the Central Research Institute of Ambulatory Health Care in Germany (Zi). ASHIP data encompasses information on billed outpatient treatments and examinations performed by SHI-accredited physicians, including diagnoses, diagnostics, examinations, and treatments (fee schedule items (GOP) of the standardized evaluation scale (EBM) and operation and procedure codes (OPS codes)). Pharmacy billing data provide additional information on prescribed medications for patients. The dataset contains information on all patients with at least one documented F-Diagnosis (mental and behavioral disorders) between Q2 2019 and Q1 2023 in the ASHIP regions corresponding to the study areas of Neuss, Frankfurt am Main, and Göppingen. Data transfer has been conducted following approved application for transmission of social data according to § 75 SGB X (German Social Code). Additionally, screening data were collected upon study inclusion, containing information on inclusion criteria, lifestyle factors, and healthcare service utilization. In the Greifswald region, a second wave of primary data collection was conducted six months after inclusion, measuring lifestyle factors, healthcare service utilization, and engagement with PSY-KOMO study components. Therefore, data from Greifswald allow for longitudinal analyses of life style factors. Screening data, ASHIP records, and pharmacy billing data are linked using identical patient pseudonyms. Data linkage is being performed via a trusted third party. The comprehensive study data enable analyses covering eight quarters before the inclusion quarter (retrospective study period) and two to eight quarters after the inclusion quarter (prospective study period) for each participant. Operationalization of endpoints Detection of new somatic diseases (H1) A new somatic disease is considered to be diagnosed or newly discovered if it is documented during the prospective observation period but was not diagnosed in the retrospective period (M2Q criterion). This is coded as a binary outcome variable (1 = at least one comorbidity newly diagnosed, 0 = no comorbidity newly diagnosed). Guideline-adherent treatment of somatic diseases (H2) Adherence to medical guidelines in the treatment of somatic diseases is operationalized using information on required physician visits, medication prescriptions, and examinations over four quarters, in accordance with relevant guidelines for each somatic comorbidity. Where applicable, patients are stratified by severity of the somatic comorbidity. This operationalization is applied if at least one somatic disease is documented in the retrospective study period. The resulting variable indicates whether all present comorbidities in an individual are treated according to medical guidelines ( 1 ) or whether none or not all of the present somatic diseases receive guideline-adherent treatment (0). Utilization of preventive and early detection Services (H3) This endpoint will be operationalized by measuring the number of preventive or early detection services utilized during the prospective study period, specifically for cases where no such services were used during the retrospective study period. The somatic diseases to be considered are listed in Table 1 . Table 1 Disease ICD-10 Codes Hepatitis C / Chronic liver disease B18.2, K70.0 - K70.3, K70.9, K74.0 - K74.2, K74,6, K74.7, K75.8, K76.1 Diabetes mellitus type 2 E11.- Coronary heart disease I20.- - I25.- Heart failure I50.- Chronic bronchitis / Asthma / COPD J41.-, J42.-, J44.-, J45.- Breast cancer C50.- Colorectal cancer C18.- - C21,- Cardiac arrhythmias incl. atrial arrhythmias I45.6, I45.8, I45.9, I47.-, I48.-, I49.- Peripheral arterial occlusive disease I70.2-, I70.8-, I70.9-, I73.8, I73.9 Arterial hypertension and secondary diseases I10.- - I13.-, I15 Sample Size Calculation Sample size calculation (package "pwr2ppl" in the statistical software R) determined that 749 patients in the intervention group (IG) were required for analyzing the primary endpoint (specifically, individuals without somatic comorbidities prior to study participation). This calculation was based on achieving 80% statistical power in a logistic regression (α = .05), with expected detection rates of somatic comorbidities of 6% in the IG compared to 3% in the control group (CG). However, at the recruitment stage, the number of patients meeting the criteria for primary endpoint analyses (absence of somatic comorbidities before participation) remains unknown. Assuming a 50% prevalence of somatic comorbidities, of which 85% are already identified before study participation, the required sample size for the IG increases to 1,302 patients. The required sample size for the matched CG was identical to that of the IG. Statistical analysis Logistic regression models have been employed to analyze the effect of PSY-KOMO care as compared to standard care on the defined endpoints and to test hypotheses H1 and H2, while a negative binomial regression has been used for hypothesis H3. These models enable statistical comparison between control and intervention group while accounting for relevant confounders that may persist despite matching (e.g., age, sex, somatic comorbidities, healthcare utilization patterns, and regional deprivation factors). The primary focus of the analysis has been on the effect of participation in PSY-KOMO (comparison between intervention and control group), which has been reported with adjustment for confounders and, where appropriate, supplemented by analyses of potential moderating effects. Changes in lifestyle factors have been analyzed using two-level mixed models, where measurement points constitute level 1 and individual participants constitute level 2. Temporal changes have been measured using time in months since study inclusion. These analyses have been adjusted for several covariates including age, sex, BMI, utilization of preventive services, primary care physician visits, specialist visits, and engagement with relevant PSY-KOMO study components. Changes in smoking status have been evaluated using McNemar tests to assess the significance of transitions between smoking categories over time. Further evaluation of the project and the PSY-KOMO care model For deeper analysis of underlying mechanisms of the implementation, a comprehensive qualitative process evaluation has been conducted, in which study participants, PSY-KOMO patient navigators and care providers were interviewed in focus groups and qualitative interviews about their experiences with and evaluation of the new form of care. A health economic evaluation of PSY-KOMO aimed at estimating the cost-effectiveness and the impact on a nationwide provision of PSY-KOMO care if the service were to become part of standard care. Furthermore, an in-depth analysis of care processes and outcomes in the study region of Neuss and Göppingen has been carried out on the basis of SHI data from two SHI companies. While the data provided by ASHIP and Zi provide are limited to outpatient data, these datasets also include e.g. hospital admissions, hospital treatment and incapacity to work. Study monitoring The intervention and data collection were accompanied by continuous study monitoring and formative evaluation of the intervention's implementation. These monitoring activities ensured that the PSY-KOMO training for the PSY-KOMO patient navigators and the recruitment of physicians at the four intervention sites were analogous. Any unexpected events and their potential consequences for patients or staff were documented and discussed at regular project meetings. Due to the non-invasive and need-oriented nature of the intervention, no termination criteria were initially defined. Discussion Current research suggests that improving access to and delivery of health care for people with SMI is essential. In order to close a gap in the use of healthcare services for people with SMI, it is important to shift the focus to promoting the use of existing healthcare resources for the general population and the referral of people with SMI to healthcare resources (Woltmann et al, 2012). The project objectives are therefore to implement and evaluate the effectiveness of the PSY-KOMO model, which aims at improving physical health care for SMI patients through a structured program involving screening by psychiatrists, targeted health support and local interdisciplinary health networks. The particular aims of PSY-KOMO care model are: ( 1 ) to develop and implement the innovative health care service model that improves the prevention and diagnosis of somatic illnesses in patients with SMI; ( 2 ) to align physical comorbidities’ treatment of SMI patients with established guidelines and medication protocols; and ( 3 ) to reduce adverse health events and improve adherence to treatment. The PSY-KOMO evaluation study has been conducted as a multicentre, non-randomized trial with an external control group. A particular advantage of PSY-KOMO is that it allows a large, regionally weighted intervention group to be compared prospectively with a retrospectively matched control group on the basis of objective billing data. However, in the given study period, longer-term desired outcomes cannot be examined (such as reduction in mortality, general medical emergencies, or hospitalization rates). A substantial body of evidence highlights the importance of improving health service utilization and promoting the physical health of people with SMI (Schneider et al, 2019; Richardson et al, 2020; McGinty et al, 2015). In a recent scoping review, Strunz et al (2022) identified 38 studies that investigated how to promote the use of existing care (i.e. beyond specific integrated care programs for people with a SMI). The authors concluded that useful interventions to promote the use of physical health care for people with a SMI exist, but appear to be still rare, or at least not accompanied by evaluation studies. This goes beyond the findings of a scoping review by Richardson et al (2020), which identified 25 studies on the broader concept of integrating physical and mental health care. More complex and multifactorial interventions, incorporating elements such as coordination with community resources, ongoing interaction with service users and the provision of person-centered care, appear to hold promise for addressing the physical health-related deficits of this population (Firth et al, 2019; Strunz et al, 2022; Richardson et al, 2020; McGinty et al, 2015). Conclusion The PSY-KOMO care intervention represents a pioneering approach to integrating mental and physical healthcare for SMI patients in the existing local health care structure through support by patient navigators and the establishment of interdisciplinary, multi-professional health networks. By focusing on the improvement of somatic disease detection, treatment and prevention in patient with SMI, the project aims to develop reliable health care models to enhance the overall quality of care for this vulnerable group and to enable them to participate in the health care system. Trial Status Intervention was active until December 2023, data collection was closed July 2024, analyses are ongoing. Declarations Ethics approval and consent to participate PSY-KOMO has been approved by the leading Ethics Committee of the Medical Faculty of the Heinrich-Heine University on 8th July 2021 (No.: 2021 − 1366). PSY-KOMO has been conducted in accordance with legal and regulatory requirements. The study has been conducted in accordance with the national statement on ethical conduct in research in accordance with Declaration of Helsinki, § 15. A detailed participant information sheet was provided to each individual and they were asked to give written informed consent. Participation was voluntary. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. PSY-KOMO Study Group Sibel Altin, Silke Andrich, Olaf Beckmann, Bettina Boshuesen, Patrick Brandenburg, Johanna Bretschneider, Dorothee Briechle, Manuela Brüne, Patrick Christ, Svenja Christians, Thomas Czihal, Nathalie Dannenmann, Simone Deininger, Verena Geffe, Sara Geis, Hans J. Grabe, Martina Hahn, Elvi Heiker-Metzger, Walter Hewer, Andrea Icks, Frank Jacobi, Naomi-Pua’nani Jiménez, Benjamin Jonas, Sarah Kaiser, Anja Kleist, Martin Köhne, Lena Köpke, Viktoria Krieger, Lars Eric Kroll, Rüdiger Kucher, Marion Kux, Verena Leve, Janina Levermann von Bardeleben, Hee-Jeong Lochmann, Corinna Lottmann, Paul Ludolph, Katharina Luett, Beate Maska, Deborah Meier, Eva Meisenzahl, Karoline Mobers, Hans-Dieter Nolting, Thorsten Nolting, Sabine Oymanns, Petra Pfisterer, Johannes Pollmanns, Maik Pommer, Ulrike Rehwald-Mohr, Andreas Reif, Sybille Roll, Vincenza Sauerwein, Lea Schmid, Frank Schneider, Catharina Scholl, Daniel Schreiber, Mandy Schulz, Nicole Spur, Andreas Stöhr, Michael Strunz, Christian Theisen, Lennart Topalov, Sarah Treffert, Anja Viehmann, Kerstin Viehmann, Rebecca Weber, Natalia Wege, Stefan Wilm, Viviane Wolf, Julia K. Wolff, Anika Zembok. Funding The study is funded by the Innovations Fund of the Federal Joint Committee in Germany (funding code: 01NVF19019). Authors' contributions The intervention and study were developed and designed by FS, WH, FJ, and SW. AV and AI drafted the manuscript, which was modified and supplemented by all other authors. Acknowledgements We would like to thank all patients, physicians/psychiatrists, patient navigators, researchers and employees of the cooperating organizations participating in the study, who have made this work possible. The following institutions are involved in the PSY-KOMO project: Institute for Health Services Research of the Medical Faculty of the Heinrich Heine University Düsseldorf, Institute of General Practice of the Medical Faculty of the Heinrich Heine University Düsseldorf, Clinic and Polyclinic for Psychiatry and Psychotherapy LVR-Klinikum Düsseldorf, Alexius/Josef Hospital Neuss, Christophsbad GmbH & Co. Hospital KG Göppingen, University Hospital Frankfurt am Main, University Medicine Greifswald, Psychologische Hochschule Berlin, Association of Statutory Health Insurance Physicians Baden-Württemberg, Association of Statutory Health Insurance Physicians Hesse, Association of Statutory Health Insurance Physicians North Rhine, Central Institute for Statutory Health Insurance Physician Care in the Federal Republic of Germany, Coordination Center for Clinical Studies University Hospital Düsseldorf (KKSD), Federal Institute for Drugs and Medical Devices (BfArM), AOK Rheinland/Hamburg, AOK Baden-Württemberg, IGES Institute GmbH Berlin . Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to German laws on privacy protection but are available from the corresponding author on reasonable request. 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Front Psychol 10:1–12 Pinnock H, Barwick M, Carpenter CR, Eldridge S, Grandes G, Griffiths CJ, Taylor SJ (2017) Standards for reporting implementation studies (StaRI) statement. BMJ 356 Prochaska JJ, Reyes RS, Schroeder SA, Daniels AS, Doederlein A, Bergeson B (2011) The smoking status of adults with serious mental illness in a psychiatric setting. J Community Health 36(2):299–305 Rethorst CD, Trivedi MH, Greer TL (2017) Sedentary behaviour and depression. Curr psychiatry Rep 19(3):1–7 Richardson A, Richard L, Gunter K, Cunningham R, Hamer H, Lockett H, Wyeth E, Stokes T, Burke M, Green M, Cox A, Derrett S (2020) A Systematic Scoping Review of Interventions to Integrate Physical and Mental Healthcare for People with Serious Mental Illness and Substance Use Disorders. J Psychiatr Res 128:52–67 Saha S, Chant D, McGrath J (2007) A systematic review of mortality in schizophrenia: Is the differential mortality gap worsening over time? Arch. Gen Psychiatry 64:1123–1131 Schneider F, Erhart M, Hewer W, Loeffler LA, Jacobi F (2019) Mortality and Medical Comorbidity in the Severely Mentally Ill. Dtsch Arztebl Int 116(23–24):405–411 Simon GE, Von Korff M, Saunders K, Miglioretti DL, Crane PK, van Belle G, Kessler RC (2006) Association between obesity and psychiatric disorders in the US adult population. Arch Gen Psychiatry 63(7):824–830 Strunz M, Jiménez NP, Gregorius L, Hewer W, Pollmanns J, Viehmann K, Jacobi F (2022) Interventions to Promote the Utilization of Physical Health Care for People with Severe Mental Illness: A Scoping Review. Int J Environ Res Public Health 20(1):126 Thornicroft G, Deb T, Henderson C (2018) Community mental health care worldwide: current status and further developments. World Psychiatry 17(3):276–286 Teasdale SB, Ward PB, Samaras K, Firth J, Stubbs B, Tripodi E, Burrows TL (2019) Dietary intake of people with severe mental illness: Systematic review and meta-analysis. Br J Psychiatry 214:251–259 Vancampfort D, Correll CU, Galling B, Probst M, De Hert M, Ward PB, Rosenbaum S, Gaughran F, Lally J, Stubbs B (2016) Diabetes mellitus in people with schizophrenia, bipolar disorder and major depressive disorder: A systematic review and large scale meta-analysis. World Psychiatry 15:166–174 Walker ER, McGee RE, Druss BG (2015) Mortality in Mental Disorders and Global Disease Burden Implications: A Systematic Review and Meta-Analysis. JAMA Psychiatry 72:334–341 Woltmann E, Grogan-Kaylor A, Perron B, Georges H, Kilbourne AM, Bauer MS (2012) Comparative effectiveness of collaborative chronic care models for mental health conditions across primary, specialty, and behavioral health care settings: systematic review and meta-analysis. Am J Psychiatry 169(8):790–804 Ziedonis DM, Williams JM, Smelson D (2003) Serious mental illness and tobacco addiction: a model program to address this issue. Am J Med Sci 326(4):223–230 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9488151","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627273439,"identity":"3b1d0e71-dfc9-49ae-9814-39b52a7422b9","order_by":0,"name":"Anja Viehmann","email":"","orcid":"","institution":"Institute for Health Services Research and Health Economics, Centre for Health and Society, Faculty of Medicine, Heinrich Heine University and University Hospital Düsseldorf, Düsseldorf, Germany","correspondingAuthor":false,"prefix":"","firstName":"Anja","middleName":"","lastName":"Viehmann","suffix":""},{"id":627273440,"identity":"c33a7cef-10ac-4a7e-aced-dccb0f58a150","order_by":1,"name":"Natalia Wege","email":"","orcid":"","institution":"Institute of General Practice, Centre for Health and Society, Faculty of Medicine, Heinrich Heine University and University Hospital Düsseldorf, Düsseldorf, Germany","correspondingAuthor":false,"prefix":"","firstName":"Natalia","middleName":"","lastName":"Wege","suffix":""},{"id":627273441,"identity":"7bcf989d-1d57-4963-a08a-773cac19038b","order_by":2,"name":"Verena Leve","email":"","orcid":"","institution":"Institute of General Practice, Centre for Health and Society, Faculty of Medicine, Heinrich Heine University and University Hospital Düsseldorf, Düsseldorf, Germany","correspondingAuthor":false,"prefix":"","firstName":"Verena","middleName":"","lastName":"Leve","suffix":""},{"id":627273442,"identity":"de92d83a-461b-4ba5-af17-99567f94475c","order_by":3,"name":"Frank Jacobi","email":"","orcid":"","institution":"Psychologische Hochschule Berlin, Berlin, Germany","correspondingAuthor":false,"prefix":"","firstName":"Frank","middleName":"","lastName":"Jacobi","suffix":""},{"id":627273443,"identity":"1792c23e-86b3-4d9e-a1be-4d8c18f98871","order_by":4,"name":"Martina Hahn","email":"","orcid":"","institution":"Department of Psychiatry, Psychotherapy and Psychosomatics, University Medicine Frankfurt, Frankfurt, Germany","correspondingAuthor":false,"prefix":"","firstName":"Martina","middleName":"","lastName":"Hahn","suffix":""},{"id":627273444,"identity":"f7d7be5d-1156-4e03-afe7-958102cabc68","order_by":5,"name":"Walter Hewer","email":"","orcid":"","institution":"Klinikum Christophsbad, Göppingen, Germany","correspondingAuthor":false,"prefix":"","firstName":"Walter","middleName":"","lastName":"Hewer","suffix":""},{"id":627273445,"identity":"9faee22a-1e65-4f54-95b1-d13b988c578a","order_by":6,"name":"Julia K. Wolff","email":"","orcid":"","institution":"IGES Institute, Berlin, Germany","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"K.","lastName":"Wolff","suffix":""},{"id":627273446,"identity":"e47dd647-0f91-4cee-8ac7-20cc4c1e0a96","order_by":7,"name":"Frank Schneider","email":"","orcid":"","institution":"Institute for History, Theory and Ethics in Medicine, Centre for Health and Society, Heinrich Heine University Düsseldorf, Düsseldorf, Germany","correspondingAuthor":false,"prefix":"","firstName":"Frank","middleName":"","lastName":"Schneider","suffix":""},{"id":627273447,"identity":"50469cd7-e14b-4307-9c2e-4cba5d76d976","order_by":8,"name":"Catharina Scholl","email":"","orcid":"","institution":"Federal Institute for Drugs and Medical Devices, Research Division, Bonn Germany","correspondingAuthor":false,"prefix":"","firstName":"Catharina","middleName":"","lastName":"Scholl","suffix":""},{"id":627273448,"identity":"49ecbf79-d231-4f43-9290-6c187da037ae","order_by":9,"name":"Stefan Wilm","email":"","orcid":"","institution":"Institute of General Practice, Centre for Health and Society, Faculty of Medicine, Heinrich Heine University and University Hospital Düsseldorf, Düsseldorf, Germany","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Wilm","suffix":""},{"id":627273449,"identity":"e16e7b93-be3f-44e6-a659-e62b73dadcb9","order_by":10,"name":"Andrea Icks","email":"data:image/png;base64,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","orcid":"","institution":"Institute for Health Services Research and Health Economics, Centre for Health and Society, Faculty of Medicine, Heinrich Heine University and University Hospital Düsseldorf, Düsseldorf, Germany","correspondingAuthor":true,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Icks","suffix":""}],"badges":[],"createdAt":"2026-04-21 19:27:06","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":true,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9488151/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9488151/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107629708,"identity":"3d272027-0418-4dde-93c4-051363b4fdde","added_by":"auto","created_at":"2026-04-23 11:25:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":211627,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9488151/v1/85db2fb2-5c43-4346-aa26-21eb89471d26.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDesign, implementation and evaluation of PSY-KOMO care - Improving the quality of treatment for people with severe mental illness to reduce physical comorbidity and prevent increased mortality: a study protocol\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eDespite significant improvements in health services and treatments, individuals with severe mental illness (SMI), including schizophrenia, bipolar disorder, and major depressive disorder, continue to exhibit substantially higher morbidity rates compared to the general population (Saha et al, 2013; Laursen et al, 2013, 2014; Chesney et al, 2014; Walker et al, 2015; Hjorth\u0026oslash;j et al, 2017; Lee et al, 2018). Remarkably, the predominant cause of mortality among those with SMI is attributed to physical conditions such as cardiovascular diseases (Correll et al, 2022; Laursen et al, 2014) and diabetes (Vancampfort et al, 2016), which are notably prevalent among SMI patients. A comprehensive meta-analysis conducted by Walker et al (2015) explored the high risk of premature mortality in individuals with SMI, reported cardiovascular diseases as a leading cause of death. According to their findings, 67.3% of deaths arise from natural causes and 17.5% from unnatural causes such as suicide (15.2% other/unkown) (Walker et al, 2015). Another meta-analysis (Hjorth\u0026oslash;j et al, 2017) reports that people with SMI have a 2-fold increased risk of all-cause mortality and a 3.5-fold increased risk of death from cardiovascular disease, with a 10\u0026ndash;20 years reduction in life expectancy compared to the general population. In addition, research has highlighted an increased risk of cancer mortality among SMI patients. While these groups do not have a higher incidence of many types of cancer compared to the general population, their cancer mortality rates are significantly higher, mostly due to delayed detection, screening inequalities and poor compliance with treatment (Kunkel et al, 1997; Kisely et al, 2008; Howard et al, 2010). Our own research group analysed physical comorbidity and excess mortality for the German SMI population for the first time (including borderline personality disorder; Schneider et al, 2019).\u003c/p\u003e \u003cp\u003eThe excess of morbidity and premature death in SMI patients involves a complex interplay of various factors. Research indicates that individuals with severe mental illness (SMI) are predisposed to unhealthy lifestyle choices, including prevalent smoking habits (Lasser et al, 2000; Ziedonis et al, 2003; Prochaska et al, 2011), sedentary lifestyle (Rethorst et al, 2017; Peeling et al, 2019) and dietary patterns with higher consumption of saturated fat and refined sugars (Teasdale et al, 2019; Costa et al, 2019). These factors increase the risk of developing obesity and the metabolic syndrome and its associated health consequences (e.g. cardiovascular disease, stroke, type 2 diabetes). Studies have shown that people with SMI are more likely to be overweight or obese than the general population (McElroy et al, 2004; Simon et al, 2006; McIntyre et al, 2019). Importantly, this is partly due to the side effects of antipsychotics, which can include weight gain, insulin resistance and dyslipidaemia. Moreover, individuals with SMI face considerable barriers in accessing healthcare (Krausz et al, 2003; De Hert et al, 2011), which can exacerbate existing health problems. Adherence to treatment remains a challenge, caused by limited understanding of the illness, concerns about potential side effects, the stigma of mental illness, and practical barriers that complicate the process of accessing appropriate medical treatment (Kohn et al, 2022). In addition, SMI patients received suboptimal care in terms of revascularisation, secondary prevention, including the prescription of statins, beta-blockers and antiplatelets, and follow-up compared with patients without a psychiatric diagnosis (Mitchell \u0026amp; Lord 2010). Furthermore, the symptomatology of severe mental illness and stigma may limit patients' access to quality medical care and impair communication with health professionals.\u003c/p\u003e \u003cp\u003eAccording to current research, improving access and provision of healthcare for individuals with SMI is an important issue. In addition, the development of evidence-based clinical guidelines is needed to facilitate the scale-up of care for physical health conditions and their risk factors in this vulnerable group (Thornicroft et al, 2018). To close this gap in the health care services utilisation in individuals with SMI, it is essential to shift the focus towards promoting the use of existing healthcare resources and the referral of those with SMI to health care resources (Woltmann et al, 2012). Yet, there remains a lack of evaluation studies documenting the effectiveness of such interventions. The interventions mostly consisted of individual support, particularly care-management and self-management strategies, with group formats sometimes being added as a supplementary element. To address the physical health-related deficiencies of this population, more complex and multifactorial interventions that incorporate elements, such as coordination with community resources, continuous interaction with service users and health care providers, and the provision of person-centred care, appear to be promising (Firth et al, 2019; Strunz et al, 2022; Richardson et al, 2020; McGinty et al, 2015). This is where the PSY-KOMO care initiative comes into action. Therefore, the project objectives are, to implement and evaluate the effectiveness of the PSY-KOMO care model, aiming at improving physical health outcomes among SMI patients through a structured program involving patient navigators and local interdisciplinary health networks.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eIn order to describe PSY-KOMO we follow the \u0026ldquo;Standards for Reporting Implementation Studies Statement\u0026rdquo; (StaRI) (Pinnock et al, 2017).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTrial Design\u003c/h2\u003e \u003cp\u003eThe impact evaluation of the PSY-KOMO intervention is conducted as a multicentre non-randomized longitudinal study with a matched external control group. The primary analysis utilized secondary data from the Association of Statutory Health Insurance Physicians (ASHIP). The evaluation is being performed by an independent evaluation agency.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThe PSY-KOMO care model was implemented in four regions in Germany, which differed in terms of settlement geography (rural, urban, mid-urban), population composition, and coverage with medical care: Frankfurt/Main, G\u0026ouml;ppingen, Greifswald, and Neuss. These sites were also spatially distributed across Germany.\u003c/p\u003e \u003cp\u003eRecruitment took place on two levels. Several healthcare institutions in a defined geographical region, such as psychiatrists in private practice) and outpatient units of psychiatric hospitals and university departments of psychiatry, respectively, were asked to participate in PSY-KOMO care and in the evaluation study. Through a study-specific training, it was ensured that the participating physicians were familiar with the PSY-KOMO care model and the study procedures, such as inclusion criteria (age\u0026thinsp;\u0026ge;\u0026thinsp;18, confirmed ICD-10 diagnosis of SMI (ICD 10-Codes: F20.x, F21.x, F22.x, F25.x, F30.x, F31.x, F32.2, F32.3, F33.2, F33.3, F60.3x), adequate language skills in German, membership in a statutory health insurance, informed consent for study participation) and exclusion criteria (relevant cognitive limitation, advanced dementia), data collection procedures, and data protection. Patients of participating psychiatrists were approached in their practices or psychiatric outpatient departments, informed, and asked to participate. Any person who met the inclusion criteria could be asked to participate in the study, regardless of their physical health status. Subjects who signed the informed consent where then either directly screened or received an appointment to undergo the screening.\u003c/p\u003e\n\u003ch3\u003eControl group\u003c/h3\u003e\n\u003cp\u003eA multivariate matching technique based on data from the ASHIP was employed to establish the external control group. The matching pool consisted of patients who met the same inclusion criteria but were treated in neighbouring regions to prevent spill-over effects. The 1:1 Nearest Neighbor matching utilized various matching variables including demographic characteristics, health status indicators (particularly physical comorbidities), and healthcare utilization patterns (both psychiatric and general medical services). The procedure combined exact matching (primarily for inclusion criteria) with caliper matching approaches. Matching algorithms was based on Mahalanobis distance calculations. The target estimand of this procedure was the Average Treatment Effect on the Treated (ATT). The balance between intervention and control group was evaluated using standardized mean differences or differences in frequency distributions.\u003c/p\u003e\n\u003ch3\u003eDescription of the PSY-KOMO intervention\u003c/h3\u003e\n\u003cp\u003e The aim of the new form of care \u0026ldquo;PSY-KOMO\u0026rdquo; is to improve the detection of physical diseases in SMI, to achieve a stronger orientation of their treatment towards guidelines, and to increase the use of preventive screening. PSY-KOMO intervention consists of several modules and is designed as an individual intervention. Within the evaluation study, the duration of the intervention was about six months from the day of inclusion and a screening for physical diseases.\u003c/p\u003e\n\u003ch3\u003ePSY-KOMO Modules\u003c/h3\u003e\n\u003cp\u003eThe new PSY-KOMO care program has a modular structure. Stage 1 must be completed by every person participating in PSY-KOMO, while elements from Stage 2 can be utilized as needed.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStage 1 \u0026ndash; Screening\u003c/h2\u003e \u003cp\u003eTrained, certified psychiatrists carry out a standardized screening for all patients after inclusion of the participants of the PSY-KOMO study. This takes place regardless of whether there are any particular risks, pre-existing conditions, expected ADRs or secondary conditions. The screening is carried out once at the beginning and represents structured, standardized history taking, medical examinations (measurement of blood pressure and weight) and documentation of prescribed medication with the help of a documentation sheet.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStage 2 – Patient Education/Prevention\u003c/h3\u003e\n\u003cp\u003eEven with unremarkable somatic findings, there is an increased risk of an additional somatic illness due to the existing severe mental illness and potentially due to lifestyle. Therefore, all interested patients are referred to locally available prevention and training measures and to standard care services, such as exercise training, smoking cessation, nutritional counselling, and vaccinations. Online modules, for example on nutrition and exercise, are offered to all patients due to their general informational nature; a target-group-specific website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.psy-komo-tut-mir-gut.de\" target=\"_blank\"\u003ewww.psy-komo-tut-mir-gut.de\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.psy-komo-tut-mir-gut.de\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) in simple language was developed for this purpose.\u003c/p\u003e\n\u003ch3\u003eFurther medical measures\u003c/h3\u003e\n\u003cp\u003eIf there is suspicion of one or more somatic illnesses appearing to be untreated or inadequately treated, patients are referred by their psychiatrists to a general practitioner or specialist for general medical diagnostics and, if necessary, treatment as part of standard care. On request, patients are supported by patient navigators in accessing further examinations and care services, either during the consultation or through a local information sheet.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePatient Navigators Module\u003c/h2\u003e \u003cp\u003ePatient navigators are introduced to support the adequate utilisation of prevention and care services, and to promote patient motivation and adherence. These guides are healthcare professionals, particularly nurses and medical assistants, who have been trained and certified for this project. Their role is to support patients through the healthcare system for a period of six months (the intervention phase), providing assistance as required and reducing barriers to accessing prevention and care services through individually tailored measures. Each patient navigator has worked at one of the four study sites.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTelephone Consultation Module for Pharmacotherapy and ADR Risk Minimization\u003c/h2\u003e \u003cp\u003eA specific medical telephone consultation service offered by LVR-Klinikum D\u0026uuml;sseldorf provides participating practitioners with advice on prescribing psychotropic and medication (including polypharmacy), adverse drug reactions (ADRs) and interactions, particularly those involving general medical and psychotropic substances. This is carried out in close collaboration with an interaction detection system established at the German Federal Institute for Drugs and Medical Devices (BfArM). Frequent and impactful ADRs and interactions are addressed in educational material (leaflets) and made available to care providers throughout the project.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRegions, Certified Physicians, and Practice Networks\u003c/h2\u003e \u003cp\u003eAt the four regional study centers, medical project staff (specialists in psychiatry) were available to the certified physicians to coordinate and support patient-centred care with the participating physicians and patient navigators.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePrimary and secondary outcomes and hypotheses\u003c/h2\u003e \u003cp\u003eThe primary outcome is the initial diagnosis of somatic diseases (disease detection; from 10 internal medical diagnoses, see below). Further outcomes are 2) treatment of somatic diseases according to guidelines and 3) utilization of preventive and early detection services. The three hypotheses of the effectiveness evaluations target the three areas detection, treatment and prevention. Compared to the control group\u0026hellip;\u003c/p\u003e \u003cp\u003eH1: the intervention is associated with higher detection and diagnostic clarification of existing somatic diseases that were previously undiagnosed (improvement in disease detection).\u003c/p\u003e \u003cp\u003e H2: the intervention is associated with a higher proportion of both already known somatic diseases and somatic diseases diagnosed for the first time during the observation period being treated according to the German guidelines for the respective diseases (improvement in guideline-based treatment).\u003c/p\u003e \u003cp\u003eH3: the intervention is associated with an increased proportion of participants utilizing preventive and early detection services.\u003c/p\u003e \u003cp\u003eIn addition, longitudinal changes in life style factors should be examined, expecting a positive effect of PSY-KOMO on change in physical activity, smoking behaviour and alcohol consumption.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eData basis and analysis periods\u003c/h2\u003e \u003cp\u003eASHIP data, including pharmacy billing records, has been utilized for analyzing the three study hypotheses. The data have been transmitted through the Central Research Institute of Ambulatory Health Care in Germany (Zi). ASHIP data encompasses information on billed outpatient treatments and examinations performed by SHI-accredited physicians, including diagnoses, diagnostics, examinations, and treatments (fee schedule items (GOP) of the standardized evaluation scale (EBM) and operation and procedure codes (OPS codes)). Pharmacy billing data provide additional information on prescribed medications for patients. The dataset contains information on all patients with at least one documented F-Diagnosis (mental and behavioral disorders) between Q2 2019 and Q1 2023 in the ASHIP regions corresponding to the study areas of Neuss, Frankfurt am Main, and G\u0026ouml;ppingen. Data transfer has been conducted following approved application for transmission of social data according to \u0026sect;\u0026nbsp;75 SGB X (German Social Code).\u003c/p\u003e \u003cp\u003eAdditionally, screening data were collected upon study inclusion, containing information on inclusion criteria, lifestyle factors, and healthcare service utilization. In the Greifswald region, a second wave of primary data collection was conducted six months after inclusion, measuring lifestyle factors, healthcare service utilization, and engagement with PSY-KOMO study components. Therefore, data from Greifswald allow for longitudinal analyses of life style factors.\u003c/p\u003e \u003cp\u003eScreening data, ASHIP records, and pharmacy billing data are linked using identical patient pseudonyms. Data linkage is being performed via a trusted third party. The comprehensive study data enable analyses covering eight quarters before the inclusion quarter (retrospective study period) and two to eight quarters after the inclusion quarter (prospective study period) for each participant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eOperationalization of endpoints\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eDetection of new somatic diseases (H1)\u003c/strong\u003e \u003cp\u003eA new somatic disease is considered to be diagnosed or newly discovered if it is documented during the prospective observation period but was not diagnosed in the retrospective period (M2Q criterion). This is coded as a binary outcome variable (1\u0026thinsp;=\u0026thinsp;at least one comorbidity newly diagnosed, 0\u0026thinsp;=\u0026thinsp;no comorbidity newly diagnosed).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eGuideline-adherent treatment of somatic diseases (H2)\u003c/strong\u003e \u003cp\u003e Adherence to medical guidelines in the treatment of somatic diseases is operationalized using information on required physician visits, medication prescriptions, and examinations over four quarters, in accordance with relevant guidelines for each somatic comorbidity. Where applicable, patients are stratified by severity of the somatic comorbidity. This operationalization is applied if at least one somatic disease is documented in the retrospective study period. The resulting variable indicates whether all present comorbidities in an individual are treated according to medical guidelines (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) or whether none or not all of the present somatic diseases receive guideline-adherent treatment (0).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eUtilization of preventive and early detection Services (H3)\u003c/strong\u003e \u003cp\u003eThis endpoint will be operationalized by measuring the number of preventive or early detection services utilized during the prospective study period, specifically for cases where no such services were used during the retrospective study period.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe somatic diseases to be considered are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICD-10 Codes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis C / Chronic liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB18.2, K70.0 - K70.3, K70.9, K74.0 - K74.2, K74,6, K74.7, K75.8, K76.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus type 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE11.-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI20.- - I25.-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI50.-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic bronchitis / Asthma / COPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJ41.-, J42.-, J44.-, J45.-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC50.-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColorectal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC18.- - C21,-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac arrhythmias incl. atrial arrhythmias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI45.6, I45.8, I45.9, I47.-, I48.-, I49.-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral arterial occlusive disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI70.2-, I70.8-, I70.9-, I73.8, I73.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArterial hypertension and secondary diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI10.- - I13.-, I15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eSample Size Calculation\u003c/h2\u003e \u003cp\u003eSample size calculation (package \"pwr2ppl\" in the statistical software R) determined that 749 patients in the intervention group (IG) were required for analyzing the primary endpoint (specifically, individuals without somatic comorbidities prior to study participation). This calculation was based on achieving 80% statistical power in a logistic regression (α\u0026thinsp;=\u0026thinsp;.05), with expected detection rates of somatic comorbidities of 6% in the IG compared to 3% in the control group (CG). However, at the recruitment stage, the number of patients meeting the criteria for primary endpoint analyses (absence of somatic comorbidities before participation) remains unknown. Assuming a 50% prevalence of somatic comorbidities, of which 85% are already identified before study participation, the required sample size for the IG increases to 1,302 patients. The required sample size for the matched CG was identical to that of the IG.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eLogistic regression models have been employed to analyze the effect of PSY-KOMO care as compared to standard care on the defined endpoints and to test hypotheses H1 and H2, while a negative binomial regression has been used for hypothesis H3. These models enable statistical comparison between control and intervention group while accounting for relevant confounders that may persist despite matching (e.g., age, sex, somatic comorbidities, healthcare utilization patterns, and regional deprivation factors). The primary focus of the analysis has been on the effect of participation in PSY-KOMO (comparison between intervention and control group), which has been reported with adjustment for confounders and, where appropriate, supplemented by analyses of potential moderating effects.\u003c/p\u003e \u003cp\u003eChanges in lifestyle factors have been analyzed using two-level mixed models, where measurement points constitute level 1 and individual participants constitute level 2. Temporal changes have been measured using time in months since study inclusion. These analyses have been adjusted for several covariates including age, sex, BMI, utilization of preventive services, primary care physician visits, specialist visits, and engagement with relevant PSY-KOMO study components. Changes in smoking status have been evaluated using McNemar tests to assess the significance of transitions between smoking categories over time.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eFurther evaluation of the project and the PSY-KOMO care model\u003c/h2\u003e \u003cp\u003eFor deeper analysis of underlying mechanisms of the implementation, a comprehensive qualitative process evaluation has been conducted, in which study participants, PSY-KOMO patient navigators and care providers were interviewed in focus groups and qualitative interviews about their experiences with and evaluation of the new form of care.\u003c/p\u003e \u003cp\u003eA health economic evaluation of PSY-KOMO aimed at estimating the cost-effectiveness and the impact on a nationwide provision of PSY-KOMO care if the service were to become part of standard care.\u003c/p\u003e \u003cp\u003e Furthermore, an in-depth analysis of care processes and outcomes in the study region of Neuss and G\u0026ouml;ppingen has been carried out on the basis of SHI data from two SHI companies. While the data provided by ASHIP and Zi provide are limited to outpatient data, these datasets also include e.g. hospital admissions, hospital treatment and incapacity to work.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eStudy monitoring\u003c/h2\u003e \u003cp\u003eThe intervention and data collection were accompanied by continuous study monitoring and formative evaluation of the intervention's implementation. These monitoring activities ensured that the PSY-KOMO training for the PSY-KOMO patient navigators and the recruitment of physicians at the four intervention sites were analogous. Any unexpected events and their potential consequences for patients or staff were documented and discussed at regular project meetings. Due to the non-invasive and need-oriented nature of the intervention, no termination criteria were initially defined.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCurrent research suggests that improving access to and delivery of health care for people with SMI is essential. In order to close a gap in the use of healthcare services for people with SMI, it is important to shift the focus to promoting the use of existing healthcare resources for the general population and the referral of people with SMI to healthcare resources (Woltmann et al, 2012). The project objectives are therefore to implement and evaluate the effectiveness of the PSY-KOMO model, which aims at improving physical health care for SMI patients through a structured program involving screening by psychiatrists, targeted health support and local interdisciplinary health networks. The particular aims of PSY-KOMO care model are: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) to develop and implement the innovative health care service model that improves the prevention and diagnosis of somatic illnesses in patients with SMI; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) to align physical comorbidities\u0026rsquo; treatment of SMI patients with established guidelines and medication protocols; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) to reduce adverse health events and improve adherence to treatment. The PSY-KOMO evaluation study has been conducted as a multicentre, non-randomized trial with an external control group. A particular advantage of PSY-KOMO is that it allows a large, regionally weighted intervention group to be compared prospectively with a retrospectively matched control group on the basis of objective billing data. However, in the given study period, longer-term desired outcomes cannot be examined (such as reduction in mortality, general medical emergencies, or hospitalization rates).\u003c/p\u003e \u003cp\u003eA substantial body of evidence highlights the importance of improving health service utilization and promoting the physical health of people with SMI (Schneider et al, 2019; Richardson et al, 2020; McGinty et al, 2015). In a recent scoping review, Strunz et al (2022) identified 38 studies that investigated how to promote the use of existing care (i.e. beyond specific integrated care programs for people with a SMI). The authors concluded that useful interventions to promote the use of physical health care for people with a SMI exist, but appear to be still rare, or at least not accompanied by evaluation studies. This goes beyond the findings of a scoping review by Richardson et al (2020), which identified 25 studies on the broader concept of integrating physical and mental health care. More complex and multifactorial interventions, incorporating elements such as coordination with community resources, ongoing interaction with service users and the provision of person-centered care, appear to hold promise for addressing the physical health-related deficits of this population (Firth et al, 2019; Strunz et al, 2022; Richardson et al, 2020; McGinty et al, 2015).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe PSY-KOMO care intervention represents a pioneering approach to integrating mental and physical healthcare for SMI patients in the existing local health care structure through support by patient navigators and the establishment of interdisciplinary, multi-professional health networks. By focusing on the improvement of somatic disease detection, treatment and prevention in patient with SMI, the project aims to develop reliable health care models to enhance the overall quality of care for this vulnerable group and to enable them to participate in the health care system.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003eTrial Status\u003c/h2\u003e \u003cp\u003eIntervention was active until December 2023, data collection was closed July 2024, analyses are ongoing.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e PSY-KOMO has been approved by the leading Ethics Committee of the Medical Faculty of the Heinrich-Heine University on 8th July 2021 (No.: 2021\u0026thinsp;\u0026minus;\u0026thinsp;1366). PSY-KOMO has been conducted in accordance with legal and regulatory requirements. The study has been conducted in accordance with the national statement on ethical conduct in research in accordance with Declaration of Helsinki, \u0026sect;\u0026nbsp;15. A detailed participant information sheet was provided to each individual and they were asked to give written informed consent. Participation was voluntary.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003ePSY-KOMO Study Group\u003c/h2\u003e \u003cp\u003eSibel Altin, Silke Andrich, Olaf Beckmann, Bettina Boshuesen, Patrick Brandenburg, Johanna Bretschneider, Dorothee Briechle, Manuela Br\u0026uuml;ne, Patrick Christ, Svenja Christians, Thomas Czihal, Nathalie Dannenmann, Simone Deininger, Verena Geffe, Sara Geis, Hans J. Grabe, Martina Hahn, Elvi Heiker-Metzger, Walter Hewer, Andrea Icks, Frank Jacobi, Naomi-Pua\u0026rsquo;nani Jim\u0026eacute;nez, Benjamin Jonas, Sarah Kaiser, Anja Kleist, Martin K\u0026ouml;hne, Lena K\u0026ouml;pke, Viktoria Krieger, Lars Eric Kroll, R\u0026uuml;diger Kucher, Marion Kux, Verena Leve, Janina Levermann von Bardeleben, Hee-Jeong Lochmann, Corinna Lottmann, Paul Ludolph, Katharina Luett, Beate Maska, Deborah Meier, Eva Meisenzahl, Karoline Mobers, Hans-Dieter Nolting, Thorsten Nolting, Sabine Oymanns, Petra Pfisterer, Johannes Pollmanns, Maik Pommer, Ulrike Rehwald-Mohr, Andreas Reif, Sybille Roll, Vincenza Sauerwein, Lea Schmid, Frank Schneider, Catharina Scholl, Daniel Schreiber, Mandy Schulz, Nicole Spur, Andreas St\u0026ouml;hr, Michael Strunz, Christian Theisen, Lennart Topalov, Sarah Treffert, Anja Viehmann, Kerstin Viehmann, Rebecca Weber, Natalia Wege, Stefan Wilm, Viviane Wolf, Julia K. Wolff, Anika Zembok.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003e The study is funded by the Innovations Fund of the Federal Joint Committee in Germany (funding code: 01NVF19019).\u003c/p\u003e\u003ch2\u003eAuthors' contributions\u003c/h2\u003e \u003cp\u003eThe intervention and study were developed and designed by FS, WH, FJ, and SW. AV and AI drafted the manuscript, which was modified and supplemented by all other authors.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe would like to thank all patients, physicians/psychiatrists, patient navigators, researchers and employees of the cooperating organizations participating in the study, who have made this work possible. The following institutions are involved in the PSY-KOMO project:\u003c/p\u003e \u003cp\u003eInstitute for Health Services Research of the Medical Faculty of the Heinrich Heine University D\u0026uuml;sseldorf, Institute of General Practice of the Medical Faculty of the Heinrich Heine University D\u0026uuml;sseldorf, Clinic and Polyclinic for Psychiatry and Psychotherapy LVR-Klinikum D\u0026uuml;sseldorf, Alexius/Josef Hospital Neuss, Christophsbad GmbH \u0026amp; Co. Hospital KG G\u0026ouml;ppingen, University Hospital Frankfurt am Main, University Medicine Greifswald, Psychologische Hochschule Berlin, Association of Statutory Health Insurance Physicians Baden-W\u0026uuml;rttemberg, Association of Statutory Health Insurance Physicians Hesse, Association of Statutory Health Insurance Physicians North Rhine, Central Institute for Statutory Health Insurance Physician Care in the Federal Republic of Germany, Coordination Center for Clinical Studies University Hospital D\u0026uuml;sseldorf (KKSD), Federal Institute for Drugs and Medical Devices (BfArM), AOK Rheinland/Hamburg, AOK Baden-W\u0026uuml;rttemberg, IGES Institute GmbH Berlin .\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to German laws on privacy protection but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChesney E, Goodwin G, Fazel S (2014) Risks of all-cause and suicide mortality in mental disorders: A meta-review. World Psychiatry 13:153\u0026ndash;160\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorrell CU, Solmi M, Croatto G, Schneider LK, Rohani-Montez SC, Fairley L, Smith N, Bitter I, Gorwood P, Taipale H, Tiihonen J (2022) Mortality in people with schizophrenia: a systematic review and meta-analysis of relative risk and aggravating or attenuating factors. World Psychiatry 21:248\u0026ndash;271\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCosta R, Teasdale S, Abreu S, Bastos T, Probst M, Rosenbaum S, Ward PB, Corredeira R (2019) Dietary Intake, Adherence to Mediterranean Diet and Lifestyle-Related Factors in People with Schizophrenia. Issues Ment Health Nurs 40:851\u0026ndash;860\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Hert M, Correll CU, Bobes J, Cetkovich-Bakmas M, Cohen D, Asai I, Detraux J, Gautam S, M\u0026ouml;ller HJ, Ndetei DM, Newcomer JW, Uwakwe R, Leucht S (2011) Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry 10(1):52\u0026ndash;77\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Hert M, Detraux J, van Winkel R, Yu W, Correll CU (2011) Metabolic and cardiovascular adverse effects associated with antipsychotic drugs. Nat Rev Endocrinol 8:114\u0026ndash;126\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFirth J, Siddiqi N, Koyanagi A, Siskind D, Rosenbaum S, Galletly C, Allan S, Caneo C, Carney R, Carvalho AF, Chatterton ML, Correll CU, Curtis J, Gaughran F, Heald A, Hoare E, Jackson SE, Kisely S, Lovell K, Maj M, McGorry PD, Mihalopoulos C, Myles H, O\u0026rsquo;Donoghue B, Pillinger T, Sarris J, Schuch FB, Shiers D, Smith L, Solmi M, Suetani S, Taylor J, Teasdale SB, Thornicroft G, Torous J, Usherwood T, Vancampfort D, Veronese N, Ward PB, Yung AR, Killackey E, Stubbs B (2019) The Lancet Psychiatry Commission: A Blueprint for Protecting Physical Health in People with Mental Illness. Lancet Psychiatry 6:675\u0026ndash;712\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHjorth\u0026oslash;j C, St\u0026uuml;rup AE, McGrath J, Nordentoft M (2017) Years of potential life lost and life expectancy in schizophrenia: A systematic review and meta-analysis. Lancet Psychiatry 4:295\u0026ndash;301\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoward LM, Barley EA, Davies E, Rigg A, Lempp H, Rose D, Taylor D, Thornicroft G (2010) Cancer diagnosis in people with severe mental illness: practical and ethical issues. Lancet Oncol 11:797\u0026ndash;804\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKisely S, Sadek J, MacKenzie A, Lawrence D, Campbell LA (2008) Excess cancer mortality in psychiatric patients. Can J Psychiatry 53:753\u0026ndash;761\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKohn L, Christiaens W, Detraux J (2022) Jan De Lepeleire 3, Marc De Hert 4 5, Benoit Gillain 6, Benjamin Delaunoit 7, Isabelle Savoye 1, Patriek Mistiaen 1, Vicky Jespers. Barriers to Somatic Health Care for Persons With Severe Mental Illness in Belgium: A Qualitative Study of Patients' and Healthcare Professionals' Perspectives. Front Psychiatry 12:798530\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrausz M, Barak Y, Grinyayev L (2003) Utilization of mental health services by persons with schizophrenia: Individual and area-level predictors. Psychiatry Res 117:165\u0026ndash;174\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKunkel EJ, Woods CM, Myers RE (1997) Consultations for 'maladaptive denial of illness' in patients with cancer: psychiatric disorders that result in noncompliance. Psychooncology 6:139\u0026ndash;149\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLasser K, Boyd JW, Woolhandler S, Himmelstein DU, McCormick D, Bor DH (2000) Smoking and mental illness: a population-based prevalence study. JAMA 284:2606\u0026ndash;2610\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaursen TM, Wahlbeck K, H\u0026auml;llgren J, Westman J, \u0026Ouml;sby U, Alinaghizadeh H, Gissler M, Nordentoft M Life expectancy and death by diseases of the circulatory system in patients with bipolar disorder or schizophrenia in the Nordic countries. PLoS One2013, 8(6), e67133\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaursen TM, Nordentoft M, Mortensen PB (2014) Excess early mortality in schizophrenia. Ann Rev Clin Psychol 10:425\u0026ndash;448\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee E, Liu J, Tu X, Palmer B, Eyler L, Jeste DA (2018) Widening Longevity Gap between People with Schizophrenia and General Population: A Literature Review and Call for Action. Schizophr Res 196:9\u0026ndash;13\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcIntyre RS, Park KY, Rasgon NL (2019) Obesity, metabolic dysfunction, and bipolar disorder: Insights from genetics. Metabolism 92:71\u0026ndash;81\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcElroy SL, Kotwal R, Malhotra S, Nelson EB, Keck PE Jr (2004) Are mood disorders and obesity related? A review for the mental health professional. J Clin Psychiatry 65(5):634\u0026ndash;651\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGinty EE, Baller J, Azrin ST, Juliano-Bult D, Daumit GL (2015) Interventions to Address Medical Conditions and Health-Risk Behaviors Among Persons with Serious Mental Illness: A Comprehensive Review. Schizophr Bull 42:96\u0026ndash;124\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitchell AJ, Lord O (2010) Do deficits in cardiac care influence high mortality rates in schizophrenia? A systematic review and pooled analysis. J Psychopharmacol 24(4 Suppl):69\u0026ndash;80\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeeling P, Binnie MJ, Goods PSR (2019) Sedentary behavior and mental health in adults: A systematic review of observational studies. Front Psychol 10:1\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePinnock H, Barwick M, Carpenter CR, Eldridge S, Grandes G, Griffiths CJ, Taylor SJ (2017) Standards for reporting implementation studies (StaRI) statement. BMJ 356\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProchaska JJ, Reyes RS, Schroeder SA, Daniels AS, Doederlein A, Bergeson B (2011) The smoking status of adults with serious mental illness in a psychiatric setting. J Community Health 36(2):299\u0026ndash;305\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRethorst CD, Trivedi MH, Greer TL (2017) Sedentary behaviour and depression. Curr psychiatry Rep 19(3):1\u0026ndash;7\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRichardson A, Richard L, Gunter K, Cunningham R, Hamer H, Lockett H, Wyeth E, Stokes T, Burke M, Green M, Cox A, Derrett S (2020) A Systematic Scoping Review of Interventions to Integrate Physical and Mental Healthcare for People with Serious Mental Illness and Substance Use Disorders. J Psychiatr Res 128:52\u0026ndash;67\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaha S, Chant D, McGrath J (2007) A systematic review of mortality in schizophrenia: Is the differential mortality gap worsening over time? Arch. Gen Psychiatry 64:1123\u0026ndash;1131\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchneider F, Erhart M, Hewer W, Loeffler LA, Jacobi F (2019) Mortality and Medical Comorbidity in the Severely Mentally Ill. 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Am J Med Sci 326(4):223\u0026ndash;230\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Innovations Fund of the Federal Joint Committee in Germany","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PSY-KOMO, study protocol, intervention study, severe mental illness, physical comorbidity, quality of treatment, patient navigator","lastPublishedDoi":"10.21203/rs.3.rs-9488151/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9488151/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Individuals with severe mental illness (SMI) have an increased risk for physical comorbidities, such as diabetes and cardiovascular disease, leading to reduced life expectancy. The overshadowing phenomenon is a major contributor to this health inequality, as clinical attention is predominantly focused on the management of psychiatric conditions, often to the detriment of physical health problems. PSY-KOMO aims at filling this gap by implementing an intervention focused on improving the prevention, detection and management of physical diseases in SMI patients through structuring the diagnostic approach of psychiatrists, providing patient navigators and building interdisciplinary health networks.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThe study design is a multicentre, non-randomized study with an intervention group (IG) receiving the new treatment PSY-KOMO care compared with a matched external control group (CG) (quasi-experimental design). Three endpoints are evaluated: (1) Improvement in the detection of physical diseases (incidence); (2) improvement in guideline-based treatment of the physical diseases; and (3) improvement of prevention and screening for physical diseases. These endpoints are compared between the IG and the external CG using regression analyses. Based on the sample size calculation, 1,302 participants with severe mental illness (SMI) were planned to be recruited for the intervention group (IG) to analyse the primary endpoint. Patients were included from four distinct regions in Germany: Frankfurt am Main, Neuss, Greifswald, and Göppingen. For analyses and matching of an external control group, data from the Association of Statutory Health Insurance Physicians are used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion: \u003c/strong\u003eThe results will be used to evaluate the effectiveness of the PSY-KOMO intervention. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e DRKS (DRKS - Deutsches Register Klinischer Studien)- Deutsches Register Klinischer Studien, DRKS00030200 registered on 27\u003csup\u003eth\u003c/sup\u003e January 2023.\u003c/p\u003e","manuscriptTitle":"Design, implementation and evaluation of PSY-KOMO care - Improving the quality of treatment for people with severe mental illness to reduce physical comorbidity and prevent increased mortality: a study protocol","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 11:24:05","doi":"10.21203/rs.3.rs-9488151/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c358fe30-06da-4d12-9c3d-759e58f088f4","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66764225,"name":"Psychiatry"},{"id":66764226,"name":"Epidemiology"}],"tags":[],"updatedAt":"2026-04-23T11:24:05+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 11:24:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9488151","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9488151","identity":"rs-9488151","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}