The Economics of Integrated Depression Care: The University of Michigan Study

A goal of the Robert Wood Johnson Depression and Primary Care Initiative at the University of Michigan is to create and implement the clinical care and financial systems necessary to enable links between primary care and mental health specialty depression care. This paper describes the economic issues related to resources required, the mechanisms to distribute those resources, and the support that must be garnered from stakeholders. By systematic measurement and application, we assess the cost, price and selected consequences of these efforts. The study illustrates the need for both centralized and distributed capacity and support for innovative models of care.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44096/1/10488_2005_Article_4231.pd

Diabetes Distress but Not Clinical Depression or Depressive Symptoms Is Associated With Glycemic Control in Both Cross-Sectional and Longitudinal Analyses

ObjectiveTo determine the concurrent, prospective, and time-concordant relationships among major depressive disorder (MDD), depressive symptoms, and diabetes distress with glycemic control.Research design and methodsIn a noninterventional study, we assessed 506 type 2 diabetic patients for MDD (Composite International Diagnostic Interview), for depressive symptoms (Center for Epidemiological Studies-Depression), and for diabetes distress (Diabetes Distress Scale), along with self-management, stress, demographics, and diabetes status, at baseline and 9 and 18 months later. Using multilevel modeling (MLM), we explored the cross-sectional relationships of the three affective variables with A1C, the prospective relationships of baseline variables with change in A1C over time, and the time-concordant relationships with A1C.ResultsAll three affective variables were moderately intercorrelated, although the relationship between depressive symptoms and diabetes distress was greater than the relationship of either with MDD. In the cross-sectional MLM, only diabetes distress but not MDD or depressive symptoms was significantly associated with A1C. None of the three affective variables were linked with A1C in prospective analyses. Only diabetes distress displayed significant time-concordant relationships with A1C.ConclusionsWe found no concurrent or longitudinal association between MDD or depressive symptoms with A1C, whereas both concurrent and time-concordant relationships were found between diabetes distress and A1C. What has been called "depression" among type 2 diabetic patients may really be two conditions, MDD and diabetes distress, with only the latter displaying significant associations with A1C. Ongoing evaluation of both diabetes distress and MDD may be helpful in clinical settings

Generalist care managers for the treatment of depressed medicaid patients in North Carolina: A pilot study

BACKGROUND: In most states, mental illness costs are an increasing share of Medicaid expenditures. Specialized depression care managers (CM) have consistently demonstrated improvements in patient outcomes relative to usual primary care (UC), but are costly and may not be fully utilized in smaller practices. A generalist care manager (GCM) could manage multiple chronic conditions and be more accepted and cost-effective than the specialist depression CM. We designed a pilot program to demonstrate the feasibility of training/deploying GCMs into primary care settings. METHODS: We randomized depressed adult Medicaid patients in 2 primary care practices in Western North Carolina to a GCM intervention or to UC. GCMs, already providing services in diabetes and asthma in both study arms, were further trained to provide depression services including self-management, decision support, use of information systems, and care management. The following data were analyzed: baseline, 3- and 6-month Patient Health Questionnaire (PHQ9) scores; baseline and 6-month Short Form (SF) 12 scores; Medicaid claims data; questionnaire on patients' perceptions of treatment; GCM case notes; physician and office staff time study; and physician and office staff focus group discussions. RESULTS: Forty-five patients were enrolled, the majority with preexisting depression. Both groups improved; the GCM group did not demonstrate better clinical and functional outcomes than the UC group. Patients in the GCM group were more likely to have prescriptions of correct dosing by chart data. GCMs most often addressed comorbid conditions (36%), then social issues (27%) and appointment reminders (14%). GCMs recorded an average of 46 interactions per patient in the GCM arm. Focus group data demonstrated that physicians valued using GCMs. A time study documented that staff required no more time interacting with GCMs, whereas physicians spent an average of 4 minutes more per week. CONCLUSION: GCMs can be trained in care of depression and other chronic illnesses, are acceptable to practices and patients, and result in physicians prescribing guideline concordant care. GCMs appear to be a feasible intervention for community medical practices and to warrant a larger scale trial to test their appropriateness for Medicaid programs nationally

Patterns of analgesic use, pain and self-efficacy: a cross-sectional study of patients attending a hospital rheumatology clinic

Background: Many people attending rheumatology clinics use analgesics and non-steroidal anti-inflammatories for persistent musculoskeletal pain. Guidelines for pain management recommend regular and pre-emptive use of analgesics to reduce the impact of pain. Clinical experience indicates that analgesics are often not used in this way. Studies exploring use of analgesics in arthritis have historically measured adherence to such medication. Here we examine patterns of analgesic use and their relationships to pain, self-efficacy and demographic factors. Methods: Consecutive patients were approached in a hospital rheumatology out-patient clinic. Pattern of analgesic use was assessed by response to statements such as 'I always take my tablets every day.' Pain and self-efficacy (SE) were measured using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Arthritis Self-Efficacy Scale (ASES). Influence of factors on pain level and regularity of analgesic use were investigated using linear regression. Differences in pain between those agreeing and disagreeing with statements regarding analgesic use were assessed using t-tests. Results: 218 patients (85% of attendees) completed the study. Six (2.8%) patients reported no current pain, 26 (12.3%) slight, 100 (47.4%) moderate, 62 (29.4%) severe and 17 (8.1%) extreme pain. In multiple linear regression self efficacy and regularity of analgesic use were significant (p < 0.01) with lower self efficacy and more regular use of analgesics associated with more pain. Low SE was associated with greater pain: 40 (41.7%) people with low SE reported severe pain versus 22 (18.3%) people with high SE, p < 0.001. Patients in greater pain were significantly more likely to take analgesics regularly; 13 (77%) of those in extreme pain reported always taking their analgesics every day, versus 9 (35%) in slight pain. Many patients, including 46% of those in severe pain, adjusted analgesic use to current pain level. In simple linear regression, pain was the only variable significantly associated with regularity of analgesic use: higher levels of pain corresponded to more regular analgesic use (p = 0.003). Conclusion: Our study confirms that there is a strong inverse relationship between self-efficacy and pain severity. Analgesics are often used irregularly by people with arthritis, including some reporting severe pain

Managed care and patient ratings of the quality of specialty care among patients with pain or depressive symptoms

BACKGROUND: Managed care efforts to regulate access to specialists and reduce costs may lower quality of care. Few studies have examined whether managed care is associated with patient perceptions of the quality of care provided by physician and non-physician specialists. Aim is to determine whether associations exist between managed care controls and patient ratings of the quality of specialty care among primary care patients with pain and depressive symptoms who received specialty care for those conditions. METHODS: A prospective cohort study design was conducted in the offices of 261 primary physicians in private practice in Seattle in 1997. Patients (N = 17,187) were screened in waiting rooms, yielding a sample of 1,514 patients with pain only, 575 patients with depressive symptoms only, and 761 patients with pain and depressive symptoms. Patients (n = 1,995) completed a 6-month follow-up survey. Of these, 691 patients received specialty care for pain, and 356 patients saw mental health specialists. For each patient, managed care was measured by the intensity of managed care controls in the patient's health plan and primary care office. Quality of specialty care at follow-up was measured by patient rating of care provided by the specialists. Outcomes were pain interference and bothersomeness, Symptom Checklist for Depression, and restricted activity days. RESULTS: The intensity of managed care controls in health plans and primary care offices was generally not associated with patient ratings of the quality of specialty care. However, pain patients in more-managed primary care offices had lower ratings of the quality of specialty care from physician specialists and ancillary providers. CONCLUSION: For primary care patients with pain or depressive symptoms and who see specialists, managed care controls may influence ratings of specialty care for patients with pain but not patients with depressive symptoms

The science of clinical practice: disease diagnosis or patient prognosis? Evidence about "what is likely to happen" should shape clinical practice.

BACKGROUND: Diagnosis is the traditional basis for decision-making in clinical practice. Evidence is often lacking about future benefits and harms of these decisions for patients diagnosed with and without disease. We propose that a model of clinical practice focused on patient prognosis and predicting the likelihood of future outcomes may be more useful. DISCUSSION: Disease diagnosis can provide crucial information for clinical decisions that influence outcome in serious acute illness. However, the central role of diagnosis in clinical practice is challenged by evidence that it does not always benefit patients and that factors other than disease are important in determining patient outcome. The concept of disease as a dichotomous 'yes' or 'no' is challenged by the frequent use of diagnostic indicators with continuous distributions, such as blood sugar, which are better understood as contributing information about the probability of a patient's future outcome. Moreover, many illnesses, such as chronic fatigue, cannot usefully be labelled from a disease-diagnosis perspective. In such cases, a prognostic model provides an alternative framework for clinical practice that extends beyond disease and diagnosis and incorporates a wide range of information to predict future patient outcomes and to guide decisions to improve them. Such information embraces non-disease factors and genetic and other biomarkers which influence outcome. SUMMARY: Patient prognosis can provide the framework for modern clinical practice to integrate information from the expanding biological, social, and clinical database for more effective and efficient care

A pilot study of an integrated mental health, social and medical model for diabetes care in an inner‐city setting: three dimensions for diabetes (3DFD)

Aims We examined the effectiveness of a service innovation, Three Dimensions for Diabetes (3DFD), that consisted of a referral to an integrated mental health, social care and diabetes treatment model, compared with usual care in improving biomedical and health economic outcomes. Methods Using a non‐randomized control design, the 3DFD model was offered in two inner‐city boroughs in London, UK, where diabetes health professionals could refer adult residents with diabetes, suboptimal glycaemic control [HbA1c ≥ 75 mmol/mol (≥ 9.0%)] and mental health and/or social problems. In the usual care group, there was no referral pathway and anonymized data on individuals with HbA1c ≥ 75 mmol/mol (≥ 9.0%) were collected from primary care records. Change in HbA1c from baseline to 12 months was the primary outcome, and change in healthcare costs and biomedical variables were secondary outcomes. Results 3DFD participants had worse glycaemic control and higher healthcare costs than control participants at baseline. 3DFD participants had greater improvement in glycaemic control compared with control participants [−14 mmol/mol (−1.3%) vs. −6 mmol/mol (−0.6%) respectively, P < 0.001], adjusted for confounding. Total follow‐up healthcare costs remained higher in the 3DFD group compared with the control group (mean difference £1715, 95% confidence intervals 591 to 2811), adjusted for confounding. The incremental cost‐effectiveness ratio was £398 per mmol/mol unit decrease in HbA1c, indicating the 3DFD intervention was more effective and costed more than usual care. Conclusions A biomedical, psychological and social criteria‐based referral system for identifying and managing high‐cost and high‐risk individuals with poor glycaemic control can lead to improved health in all three dimensions