Unique Characteristics of High-Cost Users of Medical Care With Comorbid Mental Illness or Addiction in a Population-Based Cohort

Cost structure in specialist mental healthcare: what are the main drivers of the most expensive episodes?

BACKGROUND

Mental disorders are one of the costliest conditions to treat in Norway, and research into the costs of specialist mental healthcare are needed. The purpose of this article is to present a cost structure and to investigate the variables that have the greatest impact on high-cost episodes.

METHODS

Patient-level cost data and clinic information during 2018-2021 were analyzed (N = 180,220). Cost structure was examined using two accounting approaches. A generalized linear model was used to explain major cost drivers of the 1%, 5%, and 10% most expensive episodes, adjusting for patients' demographic characteristics [gender, age], clinical factors [length of stay (LOS), admission type, care type, diagnosis], and administrative information [number of planned consultations, first hospital visits, interval between two hospital episode].

RESULTS

One percent of episodes utilized 57% of total resources. Labor costs accounted for 87% of total costs. The more expensive an episode was, the greater the ratio of the inpatient (ward) cost was. Among the top-10%, 5%, and 1% most expensive groups, ward costs accounted for, respectively, 89%, 93%, and 99% of the total cost, whereas the overall average was 67%. Longer LOS, ambulatory services, surgical interventions, organic disorders, and schizophrenia were identified as the major cost drivers of the total cost, in general. In particular, LOS, ambulatory services, and schizophrenia were the factors that increased costs in expensive subgroups. The "first hospital visit" and "a very short hospital re-visit" were associated with a cost increase, whereas "the number of planned consultations" was associated with a cost decrease.

CONCLUSIONS

The specialist mental healthcare division has a unique cost structure. Given that resources are utilized intensively at the early stage of care, improving the initial flow of hospital care can contribute to efficient resource utilization. Our study found empirical evidence that planned outpatient consultations may be associated with a reduced health care burden in the long-term.

Predicting high health-cost users among people with cardiovascular disease using machine learning and nationwide linked social administrative datasets

OBJECTIVES

To optimise planning of public health services, the impact of high-cost users needs to be considered. However, most of the existing statistical models for costs do not include many clinical and social variables from administrative data that are associated with elevated health care resource use, and are increasingly available. This study aimed to use machine learning approaches and big data to predict high-cost users among people with cardiovascular disease (CVD).

METHODS

We used nationally representative linked datasets in New Zealand to predict CVD prevalent cases with the most expensive cost belonging to the top quintiles by cost. We compared the performance of four popular machine learning models (L1-regularised logistic regression, classification trees, k-nearest neighbourhood (KNN) and random forest) with the traditional regression models.

RESULTS

The machine learning models had far better accuracy in predicting high health-cost users compared with the logistic models. The harmony score F1 (combining sensitivity and positive predictive value) of the machine learning models ranged from 30.6% to 41.2% (compared with 8.6-9.1% for the logistic models). Previous health costs, income, age, chronic health conditions, deprivation, and receiving a social security benefit were among the most important predictors of the CVD high-cost users.

CONCLUSIONS

This study provides additional evidence that machine learning can be used as a tool together with big data in health economics for identification of new risk factors and prediction of high-cost users with CVD. As such, machine learning may potentially assist with health services planning and preventive measures to improve population health while potentially saving healthcare costs.

Identifying Populations with Complex Needs: Variation in Approaches Used to Select Complex Patient Populations

Interventions to support patients with complex needs are proliferating. However, little attention has been paid to methods for identifying complex patients. This study aims to summarize approaches used to define populations with complex needs in practice, by cataloging specific population criteria and organizing them into a taxonomy. The authors conducted a pragmatic review of literature published January 2000-December 2018 using PubMed. Search results were limited to English-language studies of adults that specified a set of objective criteria to identify a population with complex needs. The authors abstracted data from each article on population parameters, and conducted thematic analysis guided by deductive coding. The review identified 70 studies reflecting 90 unique complex population definitions. Complex populations criteria reflected 3 approaches: stratification, segmentation, and targeting. Six domains of population criteria were found within, including age-based criteria (59 populations); income (12); health care costs (45); health care utilization (39); health conditions (35); and subjective criteria (15). Criteria from multiple domains were frequently used in combination, and exact specifications were highly variable within each domain. Overall, 83% of the 90 population definitions included at least 1 cost- or utilization-based criterion. Nearly every study in the review presented a unique approach to identifying patients with complex needs but a limited number of "schools of thought" were found. Variability in definitions and inconsistent terminology are potential sources of ambiguity between stakeholders. Greater specificity and transparency in complex population definition would be a substantial contribution to the emerging field of complex care.

Characteristics of health care related to mental health and substance use disorders among Community Health Centre clients in Ontario: a population-based cohort study

BACKGROUND

Community Health Centre (CHC) client populations with a history of mental illness or substance use disorders, or both, are not described well in the literature. We identified CHC clients in Ontario with a history of health care related to mental health or substance use disorders, or both, and describe their demographic characteristics, health system use and related health risks in comparison to other people in the province with similar diagnoses who did not use CHC services.

METHODS

We conducted a population-based cohort study using provincial health administrative data among Ontario residents aged 21-105 years with a previously established medical history of a mental illness or substance use disorder, or both. We examined 3 groups: clients of CHC sites that serve at-risk priority populations (PPCHCs) who presented for care at a CHC between Apr. 1, 2014, and Mar. 31, 2015, clients of CHC sites that serve nonpriority populations (NPPCHCs) who presented for care at a CHC over the same period, and a community control group of patients with a history of health care use related to mental illness or substance use disorders, or both, in the 2 years before the index date who were not CHC clients. We used descriptive statistics and multivariable logistic regression to estimate the odds of psychiatric care and emergency department use within 1 year of the index date.

RESULTS

Compared to the community control patients (n = 1 673 200), clients of PPCHCs (n = 6575) and NPPCHCs (n = 15 208) were younger, experienced more residential instability and had an increased prevalence of medical comorbidities; they had higher odds of receiving care from a psychiatrist (adjusted odds ratio [OR] 1.26, 95% confidence interval [CI] 1.20-1.33, and 1.47, 95% CI 1.41-1.53, respectively) and visiting an emergency department (adjusted OR 1.15, 95% CI 1.10-1.20, and 1.13, 95% CI 1.09-1.17, respectively) in the 1-year follow-up period.

INTERPRETATION

Ontario CHC clients with mental health or substance use disorders had medically complex needs and were intensive users of the health care system. Specific interventions should be developed to better serve this vulnerable population.

Understanding Engagement with a Physical Health Service: A Qualitative Study of Patients with Severe Mental Illness

OBJECTIVE

Individuals with severe mental illness (SMI) are disproportionally affected by medical comorbidities, resulting in poor physical health and premature death. Despite this, care for chronic medical conditions is suboptimal, and there is limited research that explores this phenomenon from the patient's perspective. The aim of this study was to identify barriers and facilitators of engagement with a physical health service experienced by individuals with SMI.

METHODS

Adults with SMI were recruited from a large psychiatric hospital and offered referral to a physical health service focused on the prevention and treatment of obesity and diabetes. Interviews were conducted at referral, 3, and 6 months. Data from 56 interviews of 24 participants were analyzed using the framework method to identify factors influencing engagement.

RESULTS

Barriers to engagement were identified at individual, medical program, and health system levels. Factors influencing the individual experience included difficulty in care coordination, affective symptomatology, and ability to bond with providers. Factors at the program level included difficulty adjusting to the clinic environment and the inability to achieve treatment goals. Factors at the system level included challenges in attending multiple appointments in a fragmented health system, lack of social support, and financial constraints.

CONCLUSIONS

This qualitative study suggests that traditional models of medical care for chronic conditions pose challenges for many individuals with SMI and contribute to health disparities. Adaptation of medical care to populations with SMI and close collaboration between medical and mental health services are necessary to improve medical care and, subsequently, health outcomes.

Prevalence of common mental health disorders in adults who are high or costly users of healthcare services: protocol for a systematic review and meta-analysis

INTRODUCTION

In all healthcare settings, a small proportion of patients account for a large level of healthcare use and associated high healthcare costs. Depression and anxiety are common co-morbidities in patients who are high users of care. The aims of this systematic review are to: (1) estimate the prevalence of anxiety/depression in adults who are high users of general physical healthcare services and/or who accrue high healthcare costs (2) estimate the magnitude of healthcare use associated with the presence of anxiety/depression.

METHODS AND ANALYSIS

This review will include any studies where patients are high users of primary, secondary or emergency healthcare services and/or accrue high healthcare costs. This is the first systematic review to focus on patients who are over the age of 18, whose degree of anxiety/depression has been evaluated with a standardised questionnaire or by a clinical interview generating a diagnosis according to international diagnostic criteria. The review will include eligible studies indexed in Medline, PsychINFO, Embase, Cumulative Index to Nursing and Allied Health Literature, Prospective Register of Systematic Reviews, Cochrane Library from inception to 1 April 2019. We will estimate the prevalence of anxiety/depression in these populations and the magnitude of use associated with anxiety/depression across various general physical healthcare settings. We will provide a narrative description of findings and factors that may influence them. A meta-analysis may be pursued if the degree of heterogeneity across studies is acceptable.

ETHICS AND DISSEMINATION

This systematic review will use data from existing studies, hence no ethical approvals are required. Findings will be disseminated in a peer-reviewed publication and at relevant academic meetings.

PROSPERO REGISTRATION NUMBER

PROSPERO CRD42018102628.

Risk factors for repetitive doctor's consultations due to cough: a cross-sectional study in a Finnish employed population

OBJECTIVES

Cough is the most common symptom prompting people to consult a doctor, thus representing a huge cost to the healthcare. This burden could be reduced by decreasing the number of repetitive consultations by the same individuals. Therefore, it would be valuable to recognise the factors that associate with repetitive doctor's consultations due to cough.

DESIGN

A cross-sectional, email survey.

SETTING

Public service employees in two Finnish towns.

PARTICIPANTS

The questionnaire was sent to 13 980 subjects; 3695 (26.4 %) participated.

INTERVENTIONS

The questionnaire sought detailed information about participant characteristics, all disorders diagnosed by a doctor, various symptoms and doctor's consultations. Those with current cough were inquired about cough characteristics and filled in the Leicester Cough Questionnaire (LCQ).

PRIMARY OUTCOME

Repetitive (≥3) doctor's consultations due to cough during the previous 12 months.

RESULTS

There were 205 participants (5.5% of the participants) with repetitive consultations. They accounted for 848 out of the 1681 doctor's consultations (50.4%) due to cough. Among all participants, repetitive consultations were mainly related to the presence of asthma (adjusted OR (aOR) 2.90 (2.01 to 4.19)) and chronic rhinosinusitis (aOR 2.40 (1.74 to 3.32)). Among the 975 participants with current cough, repetitive consultations were mainly related to a low LCQ total score (aOR 3.84 (2.76 to 5.34) per tertile). Comorbidity, depressive symptoms and smoking were also associated with repetitive consultations.

CONCLUSIONS

A modest proportion of subjects with repetitive consultations is responsible for every second doctor's consultation due to cough. The typical features of these subjects could be identified. These findings can help to focus on certain subpopulations in order to plan interventions to reduce the healthcare burden attributable to cough.

Acute Care Use for Ambulatory Care-Sensitive Conditions in High-Cost Users of Medical Care with Mental Illness and Addictions

OBJECTIVE

The role of mental illness and addiction in acute care use for chronic medical conditions that are sensitive to ambulatory care management requires focussed attention. This study examines how mental illness or addiction affects risk for repeat hospitalization and/or emergency department use for ambulatory care-sensitive conditions (ACSCs) among high-cost users of medical care.

METHOD

A retrospective, population-based cohort study using data from Ontario, Canada. Among the top 10% of medical care users ranked by cost, we determined rates of any and repeat care use (hospitalizations and emergency department [ED] visits) between April 1, 2011, and March 31, 2012, for 14 consensus established ACSCs and compared them between those with and without diagnosed mental illness or addiction during the 2 years prior. Risk ratios were adjusted (aRR) for age, sex, residence, and income quintile.

RESULTS

Among 314,936 high-cost users, 35.9% had a mental illness or addiction. Compared to those without, individuals with mental illness or addiction were more likely to have an ED visit or hospitalization for any ACSC (22.8% vs. 19.6%; aRR, 1.21; 95% confidence interval [CI], 1.20-1.23). They were also more likely to have repeat ED visits or hospitalizations for the same ACSC (6.2% vs. 4.4% of those without; aRR, 1.48; 95% CI, 1.44-1.53). These associations were stronger in stratifications by mental illness diagnostic subgroup, particularly for those with a major mental illness.

CONCLUSIONS

The presence of mental illness and addiction among high-cost users of medical services may represent an unmet need for quality ambulatory and primary care.