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Whitehorne-Smith P, Lalwani K, Martin R, Mitchell G, Milbourn B, Abel W, Burns S. A grounded theory exploration of the enablers and barriers of public healthcare access for people with comorbid serious mental and chronic physical illnesses in Jamaica. PLoS One 2024; 19:e0309678. [PMID: 39213323 PMCID: PMC11364246 DOI: 10.1371/journal.pone.0309678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 08/15/2024] [Indexed: 09/04/2024] Open
Abstract
Chronic physical illnesses (CPI) are highly prevalent among people with serious mental illnesses (PWSMI) yet people in this population experience significant challenges accessing healthcare. This study utilised a constructivist grounded theory approach to collect and analyse data related to the enablers and barriers to public healthcare access for PWSMI & CPI. Data were collected through semi-structured interviews conducted with fifty-seven participants comprising PWSMI &CPI and their caregivers, health policymakers, primary care physicians, psychiatrists, and mental health nurses. Enablers and barriers to healthcare access were represented using a socio-ecological model consisting of five levels: wider society, health system, clinician, family and community, and individual. Jamaica's free public healthcare system was the most pronounced enabler of healthcare access, while poverty, stigma, and discrimination were the most pronounced barriers. Factors such as social support, time, clinician beliefs, attitudes and training, and individual characteristics were identified as consisting of dimensions that were both enablers and barriers to healthcare access. These findings indicated that factors that influenced healthcare access for PWSMI & CPI were aligned with the social determinants of health. Improved healthcare access for PWSMI & CPI necessitates strategies that incorporate a multi-sectoral approach to address social and environmental factors influencing healthcare access across all levels of the socio-ecological model.
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Affiliation(s)
| | - Kunal Lalwani
- School of Global, Urban, and Social Studies, RMIT University, Melbourne, Australia
| | - Robyn Martin
- Department of Community Health and Psychiatry, University of the West Indies, Kingston, Jamaica
| | | | - Ben Milbourn
- School of Allied Health, Curtin University, Bentley, Western Australia, Australia
| | - Wendel Abel
- Department of Community Health and Psychiatry, University of the West Indies, Kingston, Jamaica
| | - Sharyn Burns
- School of Population Health, Curtin University, Bentley, Western Australia, Australia
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Orchard C, Lin E, Rosella L, Smith PM. Using unsupervised clustering approaches to identify common mental health profiles and associated mental health-care service-use patterns in Ontario, Canada. Am J Epidemiol 2024; 193:976-986. [PMID: 38576175 PMCID: PMC11228863 DOI: 10.1093/aje/kwae030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 02/28/2024] [Accepted: 03/28/2024] [Indexed: 04/06/2024] Open
Abstract
Mental health is a complex, multidimensional concept that goes beyond clinical diagnoses, including psychological distress, life stress, and well-being. In this study, we aimed to use unsupervised clustering approaches to identify multidimensional mental health profiles that exist in the population, and their associated service-use patterns. The data source was the 2012 Canadian Community Health Survey-Mental Health, linked to administrative health-care data; all Ontario, Canada, adult respondents were included. We used a partitioning around medoids clustering algorithm with Gower's proximity to identify groups with distinct combinations of mental health indicators and described them according to their sociodemographic and service-use characteristics. We identified 4 groups with distinct mental health profiles, including 1 group that met the clinical threshold for a depressive diagnosis, with the remaining 3 groups expressing differences in positive mental health, life stress, and self-rated mental health. The 4 groups had different age, employment, and income profiles and exhibited differential access to mental health-care services. This study represents the first step in identifying complex profiles of mental health at the population level in Ontario. Further research is required to better understand the potential causes and consequences of belonging to each of the mental health profiles identified. This article is part of a Special Collection on Mental Health.
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Affiliation(s)
- Christa Orchard
- Corresponding author: Christa Orchard, Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada ()
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Väisänen V, Linnaranta O, Sinervo T, Hietapakka L, Elovainio M. Healthcare use of young finnish adults with mental disorders - profiles and profile membership determinants. BMC PRIMARY CARE 2024; 25:238. [PMID: 38965514 PMCID: PMC11225417 DOI: 10.1186/s12875-024-02497-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 06/26/2024] [Indexed: 07/06/2024]
Abstract
BACKGROUND Comprehensive, timely, and integrated primary care services have been proposed as a response to the increased demand for mental health and substance use services especially among young people. However, little is known about the care utilization patterns of young people with mental and substance use disorders. Our aim was to characterize profiles of care use in young Finnish adults with mental or substance use disorders, and the potential factors associated with the service use profiles. METHODS Primary and specialized care visits of young adults (16-29 years) diagnosed with a psychiatric or a substance use disorder (n = 7714) were retrieved from the national health care register from years 2020 and 2021. K-Means clustering was used to detect different profiles based on the utilization of care services. Multinomial logistic regression was used to analyze the factors associated with different profiles of care use. RESULTS Five different profiles were identified: low care use (75%), and use of principally primary health care (11%), student health services (9%), psychiatric services (5%), or substance use services (1%). Female gender was associated with membership in the primary health care focused profiles (OR 2.58 and OR 1.99), and patients in the primary health care and student health services profiles were associated with a better continuity of care (OR 1.04 and OR 1.05). Substance use disorders were associated with psychiatric service use (OR: 2.51) and substance use services (OR: 58.91). Living in smaller municipalities was associated with lower service use when comparing to the largest city. CONCLUSIONS Young adults diagnosed with a psychiatric or a substance use disorder had remarkably different and heterogeneous care patterns. Most of the participants had low care utilization, indicating potential gaps in service use and care needs. Measures should be taken to ensure equal access to and availability of mental health services. The profiles that utilized the most services highlights the importance of integrated services and patient-oriented improvement of treatment.
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Affiliation(s)
- Visa Väisänen
- Finnish Institute for Health and Welfare, Welfare State Research and Reform unit, Health and Social Service System Research team, Mannerheimintie 166, Helsinki, 00300, Finland.
- Faculty of Social Sciences and Business Studies, Department of Health and Social Management, University of Eastern Finland, Yliopistonranta 8 E, Kuopio, 70210, Finland.
| | - Outi Linnaranta
- Finnish Institute for Health and Welfare, Equality unit, Mental health team, Mannerheimintie 166, Helsinki, 00300, Finland
| | - Timo Sinervo
- Finnish Institute for Health and Welfare, Welfare State Research and Reform unit, Health and Social Service System Research team, Mannerheimintie 166, Helsinki, 00300, Finland
| | - Laura Hietapakka
- Finnish Institute for Health and Welfare, Welfare State Research and Reform unit, Health and Social Service System Research team, Mannerheimintie 166, Helsinki, 00300, Finland
| | - Marko Elovainio
- Finnish Institute for Health and Welfare, Welfare State Research and Reform unit, Health and Social Service System Research team, Mannerheimintie 166, Helsinki, 00300, Finland
- Faculty of Medicine, Research Program Unit, Department of Psychology, University of Helsinki, Haartmaninkatu 3, Helsinki, 00014, Finland
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Shvetcov A, Whitton A, Kasturi S, Zheng WY, Beames J, Ibrahim O, Han J, Hoon L, Mouzakis K, Gupta S, Venkatesh S, Christensen H, Newby J. Machine learning identifies a COVID-19-specific phenotype in university students using a mental health app. Internet Interv 2023; 34:100666. [PMID: 37746637 PMCID: PMC10511781 DOI: 10.1016/j.invent.2023.100666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 06/19/2023] [Accepted: 09/07/2023] [Indexed: 09/26/2023] Open
Abstract
Background Advances in smartphone technology have allowed people to access mental healthcare via digital apps from wherever and whenever they choose. University students experience a high burden of mental health concerns. Although these apps improve mental health symptoms, user engagement has remained low. Studies have shown that users can be subgrouped based on unique characteristics that just-in-time adaptive interventions (JITAIs) can use to improve engagement. To date, however, no studies have examined the effect of the COVID-19 pandemic on these subgroups. Objective Here, we sought to examine user subgroup characteristics across three COVID-19-specific timepoints: during lockdown, immediately following lockdown, and three months after lockdown ended. Methods To do this, we used a two-step machine learning approach combining unsupervised and supervised machine learning. Results We demonstrate that there are three unique subgroups of university students who access mental health apps. Two of these, with either higher or lower mental well-being, were defined by characteristics that were stable across COVID-19 timepoints. The third, situational well-being, had characteristics that were timepoint-dependent, suggesting that they are highly influenced by traumatic stressors and stressful situations. This subgroup also showed feelings and behaviours consistent with burnout. Conclusions Overall, our findings clearly suggest that user subgroups are unique: they have different characteristics and therefore likely have different mental healthcare goals. Our findings also highlight the importance of including questions and additional interventions targeting traumatic stress(ors), reason(s) for use, and burnout in JITAI-style mental health apps to improve engagement.
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Affiliation(s)
| | | | | | - Wu-Yi Zheng
- Black Dog Institute, UNSW, Sydney, NSW, Australia
| | | | - Omar Ibrahim
- Black Dog Institute, UNSW, Sydney, NSW, Australia
| | - Jin Han
- Black Dog Institute, UNSW, Sydney, NSW, Australia
| | - Leonard Hoon
- Applied Artificial Intelligence Institute, Deakin University, Geelong, VIC, Australia
| | - Kon Mouzakis
- Applied Artificial Intelligence Institute, Deakin University, Geelong, VIC, Australia
| | - Sunil Gupta
- Applied Artificial Intelligence Institute, Deakin University, Geelong, VIC, Australia
| | - Svetha Venkatesh
- Applied Artificial Intelligence Institute, Deakin University, Geelong, VIC, Australia
| | | | - Jill Newby
- Black Dog Institute, UNSW, Sydney, NSW, Australia
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Desmet K, Bracke P, Deproost E, Goossens PJJ, Vandewalle J, Vercruysse L, Beeckman D, Van Hecke A, Kinnaer LM, Verhaeghe S. Associated factors of nurse-sensitive patient outcomes: A multicentred cross-sectional study in psychiatric inpatient hospitals. J Psychiatr Ment Health Nurs 2023; 30:1231-1244. [PMID: 37409521 DOI: 10.1111/jpm.12951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 06/06/2023] [Accepted: 06/22/2023] [Indexed: 07/07/2023]
Abstract
WHAT IS ALREADY KNOWN?: The nurse-patient relationship in mental health care is an important focus of mental health nursing theories and research. There is limited evidence about which factors influence nurse-sensitive patient outcomes of the nurse-patient relationship. This hinders the development, planning, delivering, and quality assurance of the nurse-patient relationship in nursing practice and nursing education. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: To our best knowledge, this is the first study to examine associations between nurse-sensitive patient outcomes of the nurse-patient relationship and a range of patient characteristics and relationship-contextual factors. In this study, we found that gender, age, hospital characteristics, nurse availability when needed, nurse contact, and nurse stimulation were associated with the scores on the nurse-sensitive patient outcome scale. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Having insight into the factors associated with nurse-sensitive patient outcomes of the nurse-patient relationship can help nurses, nursing students, nursing management and also patients to enhance the nurse-patient relationship, trying to influence outcomes of nursing care. ABSTRACT: Introduction The lack of evidence on patient characteristics and relational-contextual factors influencing nurse-sensitive patient outcomes of a nurse-patient relationship is a possible threat to the quality and education of the nurse-patient relationship. Aim To measure nurse-sensitive patient outcomes of the nurse-patient relationship and to explore the associations between nurse-sensitive patient outcomes and a range of patient characteristics and relational-contextual factors. Method In a multicenter cross-sectional study, 340 inpatients from 30 units in five psychiatric hospitals completed the Mental Health Nurse-Sensitive Patient Outcome Scale. Descriptive, univariate and Linear Mixed Model analyses were conducted. Results Overall, patient-reported outcomes were moderate to good. Female participants, nurse availability when needed, more nurse contact and nurse stimulation were associated with higher outcomes. Age differences were observed for some of the outcomes. Outcomes also varied across hospitals but were not related to the number of times patients were hospitalized or to their current length of stay in the hospital. Discussion The results may help nurses to become more sensitive and responsive to factors associated with nurse-sensitive patient outcomes of the nurse-patient relationship. Implications The nurse-sensitive results can support nurses in designing future nurse-patient relationships.
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Affiliation(s)
- Karel Desmet
- University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
- AZ Damiaan, Ostend, Belgium
| | - Piet Bracke
- Department of Sociology, Ghent University, Ghent, Belgium
| | - Eddy Deproost
- University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
- Centre for Psychiatry and Psychotherapy Clinic Sint-Jozef, Pittem, Belgium
| | - Peter J J Goossens
- University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
- Dimence Mental Health Center for Bipolar Disorder, Deventer, the Netherlands
| | | | - Lieke Vercruysse
- Centre for Psychiatry and Psychotherapy Clinic Sint-Jozef, Pittem, Belgium
| | - Dimitri Beeckman
- University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
- School of Health Sciences, Örebro University, Örebro, Sweden
- School of Nursing & Midwifery, Royal College of Surgeons in Ireland (RCSI), Dublin, Ireland
- Research Unit of Plastic Surgery, Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
- School of Nursing and Midwifery, Monash University, Melbourne, Victoria, Australia
| | - Ann Van Hecke
- University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
- Nursing Department, Ghent University Hospital, Ghent, Belgium
| | - Lise-Marie Kinnaer
- University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Sofie Verhaeghe
- University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
- Department of Nursing, VIVES University College, Roeselare, Belgium
- Faculty of Medicine and Life Science, University Hasselt, Hasselt, Belgium
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Blomgren J, Jäppinen S, Perhoniemi R. Identifying user profiles of healthcare, social and employment services in a working-age population: A cluster analysis with linked individual-level register data from Finland. PLoS One 2023; 18:e0293622. [PMID: 37910556 PMCID: PMC10619802 DOI: 10.1371/journal.pone.0293622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 10/17/2023] [Indexed: 11/03/2023] Open
Abstract
A thorough understanding of the use of services in the population is important in order to comprehend the varying service needs of different groups. This explorative study aimed to find distinct user profiles in a working-age population based on individuals' annual use of healthcare, social and employment services and to explore socio-demographic and morbidity-related predictors of the user groups. Administrative register data on the use of various services and individual-level covariates from year 2018 were linked for all residents aged 18-64 of the municipality of Oulu, Finland (N = 119,740). K-means cluster analysis was used to group the study subjects into clusters, based on their frequency of using 22 distinct healthcare, social and employment services during 2018. Multinomial logistic regression models were utilized to assess the associations of cluster assignment with socio-demographic and health-related covariates (sex, age, marital status, education, occupational class, income, days in employment, chronic disease and receipt of different social benefits). Five distinct clusters were identified in terms of service use, labelled low to moderate users of healthcare (82.0%), regular employment services users with moderate use of healthcare (9.6%), supported employment services users with moderate use of healthcare with an emphasis on preventive care (2.9%), frequent users of healthcare, social and employment services (2.9%), and rehabilitation, disability services and specialized healthcare users (2.6%). Each cluster not only showed different patterns of service use but were also differently associated with demographic, socio-economic and morbidity-related covariates, creating distinct service user types. Knowledge on the different user profiles and their determinants may help predict future need and use of services in a population, plan timely, coordinated and integrated services, and design early interventions and prevention measures. This is important in order to save costs and improve the effectiveness of services for groups with different care needs.
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Affiliation(s)
- Jenni Blomgren
- Research Unit, The Social Insurance Institution of Finland, Helsinki, Finland
| | - Sauli Jäppinen
- Analytics Unit, The Social Insurance Institution of Finland, Helsinki, Finland
| | - Riku Perhoniemi
- Research Unit, The Social Insurance Institution of Finland, Helsinki, Finland
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Classifying children with ASD by service utilization and treatment type: A cluster analysis of a nationally representative United States survey. Acta Psychol (Amst) 2023; 232:103800. [PMID: 36502602 DOI: 10.1016/j.actpsy.2022.103800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 11/15/2022] [Accepted: 12/01/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND If there are patterns of the distribution of services and treatments across the population of people with ASD, these patterns should be based along clinical characteristics or other service needs and not sociodemographic characteristics unrelated to evidence-based care. We examined how individuals in a broad, nationally representative sample "grouped together" based on service utilization and services needed but not covered by insurance. By understanding various treatment patterns, clinicians, researchers, policymakers, and self-advocates and their families can better advocate for high-quality, evidence-based services to be provided equitably. METHODS Using the 2011 Survey of Pathways to Diagnosis and Services, a cluster analysis was performed to explore patterns in this population based on medication use, private services use, school-based service use, and services not covered by insurance. Differences in clusters were then explored through multinomial logistic regression. RESULTS Six clusters emerged, showing differences in the level of service/medication usage and insurance coverage. Differences across clusters were associated with the level of functional limitation and age at ASD diagnosis. Disparities by insurance type, functional limitation, and age at diagnosis exist among patterns of ASD service provision. CONCLUSIONS Our analysis showed that intervention for children with ASD can be across several scales - high and low users of services (both private and school-based), high and low users of medications, and high and low levels of reported non-covered services. The differences were clustered in multiple ways. Further research should incorporate longitudinal and nationally representative data to explore these relationships further.
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EISI: Extended inter-spike interval for mental health patients clustering based on mental health services and medications utilisation. Med Eng Phys 2022; 110:103780. [PMID: 35232678 DOI: 10.1016/j.medengphy.2022.103780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 12/23/2021] [Accepted: 02/17/2022] [Indexed: 01/18/2023]
Abstract
Mental health is vital in all human life stages, and managing mental healthcare service resources is crucial for providers. This paper presents a new method, called Extended Inter-Spike Interval (EISI), on identifying the patients with a similar utilisation of mental health services and medications. The EISI measures the distance between the utilisation patterns of the patients. Then, the pairwise distances are given to a developed split-and-merge Partitioning Around Medoids (PAM) clustering algorithm to identify the patients with similar utilisation patterns. To evaluate the proposed method, we use two years (2013-2014) of the 10% publicly available sample of the Australian Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) administrative data. Results show that mental health patients can be grouped into ten clusters with distinct and interpretable utilisations patterns. The largest cluster comprises individuals who only visit general practitioners and take psycholeptics medications for a short time. The smallest group contains occasional visits with general practitioners and regularly utilises psycholeptics and psychoanaleptics medications over long periods. The proposed method provides insights on whom to target and how to structure services for different groups of individuals with mental health conditions.
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Kreindler S, Aboud Z, Hastings S, Winters S, Johnson K, Mallinson S, Brierley M. How Do Health Systems Address Patient Flow When Services Are Misaligned With Population Needs? A Qualitative Study. Int J Health Policy Manag 2022; 11:1362-1372. [PMID: 33949820 PMCID: PMC9808352 DOI: 10.34172/ijhpm.2021.36] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 03/30/2021] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Patient flow through health services is increasingly recognized as a system issue, yet the flow literature has focused overwhelmingly on localized interventions, with limited examination of system-level causes or remedies. Research suggests that intractable flow problems may reflect a basic misalignment between service offerings and population needs, requiring fundamental system redesign. However, little is known about health systems' approaches to population-capacity misalignment, and guidance for system redesign remains underdeveloped. METHODS This qualitative study, part of a broader investigation of patient flow in urban Western Canada, explored health-system strategies to address or prevent population-capacity misalignment. We conducted in-depth interviews with a purposive sample of managers in 10 jurisdictions across 4 provinces (N = 300), spanning all healthcare sectors and levels of management. We used the constant comparative method to develop an understanding of relevant strategies and derive principles for system design. RESULTS All regions showed evidence of pervasive population-capacity misalignment. The most superficial level of response - mutual accommodation (case-by-case problem solving) - was most prevalent; capacity (re)allocation occurred less frequently; population redefinition most rarely. Participants' insights yielded a general principle: Define populations on the basis of clusters of co-occurring need. However, defining such clusters demands a difficult balance between narrowness/rigidity and breadth/flexibility. Deeper analysis suggested a further principle: Populations that can be divided into homogeneous subgroups experiencing similar needs (eg, surgical patients) are best served by narrow/ rigid models; heterogeneous populations featuring diverse constellations of need (eg, frail older adults) require broad/ flexible models. CONCLUSION To remedy population-capacity misalignment, health system planners should determine whether clusters of population need are separable vs. fused, select an appropriate service model for each population, allocate sufficient capacity, and only then promote mutual accommodation to address exceptions. Overreliance on case-by-case solutions to systemic problems ensures the persistence of population-capacity misalignment.
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Affiliation(s)
- Sara Kreindler
- Department of Community Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada
- George & Fay Yee Centre for Healthcare Innovation, Winnipeg Regional Health Authority/University of Manitoba, Winnipeg, MB, Canada
| | - Zaid Aboud
- Department of Community Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada
| | - Stephanie Hastings
- Health Systems Evaluation & Evidence, Alberta Health Services, Calgary, AB, Canada
| | - Shannon Winters
- George & Fay Yee Centre for Healthcare Innovation, Winnipeg Regional Health Authority/University of Manitoba, Winnipeg, MB, Canada
| | - Keir Johnson
- George & Fay Yee Centre for Healthcare Innovation, Winnipeg Regional Health Authority/University of Manitoba, Winnipeg, MB, Canada
| | - Sara Mallinson
- Health Systems Evaluation & Evidence, Alberta Health Services, Calgary, AB, Canada
| | - Meaghan Brierley
- Health Systems Evaluation & Evidence, Alberta Health Services, Calgary, AB, Canada
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Gómez-de-Regil L, Estrella-Castillo DF, Cicero-Ancona M. Anxiety/Depression Predominance in Liaison-Psychiatry Users of a South-East Mexico Tertiary Hospital. Healthcare (Basel) 2022; 10:healthcare10071162. [PMID: 35885689 PMCID: PMC9322849 DOI: 10.3390/healthcare10071162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 05/30/2022] [Accepted: 06/02/2022] [Indexed: 11/16/2022] Open
Abstract
Patients at tertiary hospitals may find themselves in need of mental health support due to the distress associated with the illness that may or not lead to a psychiatric condition. Here is an overview of the clinical cases treated by the liaison psychiatry service of a public tertiary hospital from Southeast Mexico during its first years of operation (2008–2018), with the purpose of gathering information about the status and needs of this population. A sample of 304 clinical records of patients treated for the first time by the psychiatry service was reviewed, and the distribution by demographic characteristics, diagnosis of mental illness and medical area of reference was analyzed. Anxiety and depression symptoms were the most frequent. Most patients were women, lived in Merida and returned after the first appointment. The neurology service referred most patients, yet most attended directly. General tertiary hospitals should prioritize integrating ad hoc mental and physical health care. Adult women with a profile of anxiety and/or depression would be the first target group. Some areas of opportunity for further research and improvement of mental health services are: preventive services for anxiety and depression, follow-up of patients, attention to relatives of patients at intensive care units, implementation of telehealth alternatives, training on mental health screening and inter- and intra-institutional collaboration.
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Affiliation(s)
- Lizzette Gómez-de-Regil
- Hospital Regional de Alta Especialidad de la Península de Yucatán, Mérida 97130, Mexico;
- Correspondence:
| | | | - Miguel Cicero-Ancona
- Hospital Regional de Alta Especialidad de la Península de Yucatán, Mérida 97130, Mexico;
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Simo B, Bamvita JM, Caron J, Fleury MJ. Predictors of mental health service use among individuals with high psychological distress and mental disorders. Psychiatry Res 2018; 270:1122-1130. [PMID: 30360914 DOI: 10.1016/j.psychres.2018.10.019] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 08/24/2018] [Accepted: 10/08/2018] [Indexed: 02/06/2023]
Abstract
This study identified predictors of mental health service use over 12 months among 746 individuals with mental disorders and high psychological distress from a catchment area in southwest Montreal, Quebec (Canada). Data collected in 2011 and 2014 were analyzed using Andersen's Behavioral Model of Health Services Use. A hierarchical logistic regression identified predictors of mental health service use. In all, 29% of participants reported using mental health services in the previous 12 months. Three key enabling variables predicted mental health service use: having a family doctor, previous experience with mental health services, and employment. Self-perception of mental health, stressful events, and unmet needs marginally (Needs factors: non-clinical variables) were also associated with the outcome variable. Mental health service utilization depends primarily on organization of the health system, and patient perceptions of its condition (non-clinical needs). Mental health policy should focus on increasing the availability of services and professionals, especially family doctors. Other measures for encouraging service use and overall population wellbeing include raising public awareness around the signs and symptoms of mental illness as a way to promote more rapid response to patient needs, and protecting workplace mental health by reducing stress and stigma toward individuals affected by mental distress.
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Affiliation(s)
- Béatrice Simo
- École de santé publique, Université de Montréal, 7101 av. du Parc, Montreal, QC H3X1X9, Canada
| | - Jean-Marie Bamvita
- Douglas Mental Health University Institute Research Centre, 6875 LaSalle Blvd, Montreal, QC H4H 1R3, Canada
| | - Jean Caron
- Douglas Mental Health University Institute Research Centre, 6875 LaSalle Blvd, Montreal, QC H4H 1R3, Canada; Department of Psychiatry, McGill University, 1033, Pine Avenue West, Montreal, QC H3A 1A1, Canada
| | - Marie-Josée Fleury
- Douglas Mental Health University Institute Research Centre, 6875 LaSalle Blvd, Montreal, QC H4H 1R3, Canada; Department of Psychiatry, McGill University, 1033, Pine Avenue West, Montreal, QC H3A 1A1, Canada.
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