Serious mental illnesses , which typically include bipolar dis orders and schizophrenia, are characterized as chronic and debilitating conditions that place significant burdens on patients, as well as their families and society. Despite the marked improvement in managing destabilizing symptoms that followed the introduction of psychotropic medications, most patients who suffer from a SMI continue to have a limited recovery and experience poor physical health. Fifty to 80% of individuals with SMI have one or more comorbid medical conditions that may worsen prognosis and contribute to high morbidity and premature mortality. More concerning is that over 60% of the medical comorbidities observed among persons with SMIs are non fatal and preventable, yet these persons have 15 to 25 years shorter expectancy relative to the general population. Unfortunately, the medical needs of those with SMI are often neglected, which may partly explain the reason for why their morbidity and mortality are elevated. Studies of modifiable risk factors suggest that risky sexual behaviors and poor hygiene, are linked with higher risk of genitourinary, infectious, and blood borne diseases among individuals with SMIs. In creased rates of alcohol and illicit drug use, smoking, poor nutrition and lack of exercise, may be associated with higher rates of cardiovascular and respiratory conditions; and genitourinary and metabolic diseases. Patients with SMI also present for treatment with a number of serious and chronic medical conditions, and these conditions can onset up to 10 years earlier in this population compared to age matched controls. In addition,greenhouse benches having medical comorbidities place SMI patients at risk of repeat hospital visits that raise health care costs and increase the burden of disease. Not surprisingly, the problem of medical comorbidities in SMI is now considered a major public health issue due to its destabilizing effects and high cost to families and society.
Patients with SMI continue to experience elevated morbidity despite the identification of several preventable and modifiable risk factors for poor health. Thus, a study that seeks to examine associations among patients with SMI and odds of having medical comorbidities in a large integrated health system is important to inform patient care. In this study, we examined associations among 25,090 patients with a SMI diagnosis of bipolar disorder or schizophrenia and odds of having medical comorbidities relative to 25,090 patients without an SMI in a large health system. Importantly, to inform patient care planning we examined acute conditions, which are more likely to require immediate medical attention as well as severe or chronic conditions necessitating ongoing monitoring and management.Kaiser Permanente of Northern California is a nonprofit, integrated health care delivery system providing health care services to > 4 million members, serving 45% of the commercially insured population in the region. KPNC consists of a health care plan, a sole medical group, and a hospital system. Specialty health services, such as psychiatry, substance use treatment, and other specialty care, are available to all members internally. To facilitate integrated health care services, providers have access to a mature electronic health record system with each member’s medical history, including primary care, emergency department, ambulatory, hospital and specialty health care encounters. In KPNC, about 88% of members are commercially insured, 28% have Medicare and 10% have Medicaid coverage. All patients were selected from the KPNC membership for this study. Institutional review board approval was obtained from the Kaiser Foundation Research Institute.We used EHR data for this secondary, database study. These data were used to identify all health system members who 1) were at least 18 years of age, 2) had a visit to a KPNC facility in 2010, and 3) had a recorded ICD-9 diagnosis of schizophrenia or bipolar disorder in 2010. The first mention of each ICD-9 diagnosis of schizophrenia or bipolar recorded from January 1, 2010 to December 2010 were included; patients in the sample could have multiple diagnoses . We also included all current or existing behavioral health diagnoses that were additionally documented for patients with schizophrenia or bipolar during health system visits in 2010 . EHR data were also used to identify control patients without current or existing behavioral health diagnoses.
Control patients were selected for all unique patients with bipolar disorder or schizophrenia, and matched one-to-one on gender, age, and medical home facility . This method ac counted for any differences in services, types of conditions, or unobservable differences by geographic location. The final analytical sample consisted of 50,180 patients: 20,308 with bipolar disorder, 4782 with schizophrenia, and 25, 090 controls. Institutional review board approval was obtained from the Kaiser Foundation Research Institute.Age, gender, race/ethnicity, patient medical home facility, census based median neighborhood household income, and ICD-9 psychiatric and medical diagnoses were extracted from the EHR. Race/ethnicity consisted of five categories: white, Black, Hispanic, Asian, and other. Psychiatric and medical diagnoses were determined based on ICD-9 diagnoses noted during visits made over the study period and included current and existing diagnoses.Frequencies and means were used to characterize the sample. We used McNemar’s test and paired sample t-tests to determine potential differences between the matched samples of patients with SMI and controls. These analyses proceeded by examining potential differences between patients with SMI compared to controls by age, gender, race/ ethnicity and income. A series of conditional logistic regressions were then computed, predicting each of nine medical condition categories from bipolar or schizophrenia , to compare the odds associated with having medical comorbidities in patients with SMI compared to controls. We then computed a series of conditional logistic regressions predicting each of fifteen chronic or severe medical conditions from having bipolar or schizophrenia , to com pare the odds of having chronic or severe medical comorbidities in SMI patients versus controls. All conditional logistic regressions adjusted for race/ethnicity and income. SMI and control samples were matched 1- to-1 on age and gender; and thus, no significant differences were anticipated or found between matched groups regarding these relation ships .The Hochberg method was used to adjust for multiple inference testing within each medical condition category. We report Hochberg adjusted p-values for the conditional logistic regressions comparing the odds of having medical comorbidities for patients with SMI and controls. Statistical significance was defined at p < 0.05; analyses were performed using R version 2.15.0.Overall, the sample was 70.0% women, 60.0% White, 15.6% Hispanic, 12.2% Asian, 7.4% Black, 4.8% other race/ethnicity. Patients were 49 years old on average.
As shown in Table 1, more patients with schizophrenia or bipolar were white compared to controls; fewer controls were Hispanic, Asian, or Black relative to patients with schizophrenia or bipolar. However, more patients with schizophrenia were Black relative controls. On average, patients with bipolar or schizophrenia lived in lower income neighborhoods compared to controls. Since patients were matched on age and gender,growers equipment no evidence of differences across these measures were found among the controls and the patients with schizophrenia or bipolar .The high prevalence of medical comorbidities among patients with SMI constitutes major clinical and public health problems that have not been adequately addressed in specialty mental health programs or by mainstream health care. This issue is further compounded in individuals who have a SMI by problems associated with substandard living conditions and lack of access to routine health care services, which increase the risk of having unidentified and untreated medical conditions. Lack of preventative health care in combination with high risk health behaviors among individuals with SMI place them at increased risk of several serious and chronic medical conditions. Patients with SMI remain at risk for elevated morbidity and mortality, despite that health care reform in the U.S. has increased health care service access for this population in recent years. Given the increased likelihood for individuals with SMI to have poor health and poor health outcomes despite policy and clinical intervention, obtaining current information on the degree to which having a SMI is associated with a range of medical comorbidities from large health systems which manage these persons is critical to tailor future disease prevention efforts, early diagnosis, and treatment to their needs. To inform patient care and service planning, we examined acute and chronic medical conditions in SMI patients in a large integrated health system, where SMI patients potentially may have better access to health services than in health care systems where services are not integrated. Prior to our primary analyses, we investigated potential socioeconomic differences between controls and SMI patients. Since patients with SMI and the controls were matched by age and gender no differences were anticipated or found regarding these characteristics. Patients with SMI tended to be white relative to controls, except that more patients with schizophrenia were Black. Higher rates of Black patients with schizophrenia are largely consistent with prior research, and may be in part due to the over-diagnosis of Black persons with this disorder. Also consistent with prior work, we found more SMI patients were located in lower-income neighborhood KPNC service areas than controls. Prior work has found poor socioeconomic status can dramatically limit access to health care and increase exposure to unhealthy behaviors and lifestyles. This phenomenon may partly explain the reason for why having a SMI was disproportionately associated with higher likelihood of having almost all medical co morbidities and serious or chronic conditions examined relative to controls. Notably, while all controls and patients with a SMI had broad access to a range of health services , lower income for patients with SMI may disproportionately affect their ability to support transportation costs for health system visits and follow-up preventive care, and impact health outcomes.
It will be important for future work to more fully examine the role of income in predicting health care access and associated health outcomes in the SMI population. Perhaps in part related to access and low SES, our findings also revealed the odds associated with having acute and chronic medical conditions may not be the same for everyone with a SMI. Even given differences in study design, types of health care systems and samples studied, our results were largely consistent with prior work that has found patients with schizophrenia are at high risk of having endocrine or immune diseases. Patients with schizophrenia were more likely to have endocrine or immunity dis eases, as well as diabetes and obesity. While we could not address causal relationships with our design, the odds associated with having schizophrenia to obesity and diabetes has been linked to the use of some second-generation antipsychotic medications. This is problematic and concerning, as the long-term use of second-generation antipsychotic medications combined with obesity and adverse lifestyle behavior have been linked with higher odds of serious cardiovascular events in patients with schizophrenia and other SMI patient groups. These phenomena may potentially explain the reason for why we found that having schizophrenia was associated with higher odds of having a serious cardiovascular event, such as stroke. Future longitudinal work in this area is warranted, and will need to focus on isolating predisposing conditions and other risk factors associated with future cardiovascular events and mortality in schizophrenia. Although far in excess of control patients, the prevalence of cardiovascular disease and predisposing conditions such as diabetes, hypertension, and obesity in our bipolar sample was slightly below prior reports. Nevertheless, having bipolar was still associated with higher odds of conditions predisposing cardiovascular disease. Notably, these findings may in part explain the reason for why we also found having bipolar was associated with higher likelihood of serious cardiovascular events, including stroke. These findings are of interest be cause cardiovascular mortality is a leading cause of elevated mortality in patients with bipolar, and is well above the risk associated with unnatural causes of death such as injury and suicide. Consequently, future work in this area is warranted, and will need to determine the risk of cardiovascular disease to future cardiovascular events and car diovascular mortality in bipolar, as well as whether the rates of cardiovascular mortality may be lower in patients with bipolar in integrated health systems than the general population and other health care systems.Overall, having bipolar and schizophrenia was associated with high odds of blood borne and infectious disease and of hepatitis C. Although we did not examine routes of transmission, injection drug use, high risk sexual behaviors, or comorbid substance use, SMI patients have been found to exhibit this behavior, raising the odds of blood borne and infectious disease and hepatitis C. While substantially higher than the control estimates, the prevalence of hepatitis C in our sample fell below previously published rates of hepatitis C in individuals with SMI.