The results of this study support the hypothesis that GC improves important dimensions of the quality of chronic health care experienced by multi-morbid older persons. Health-care processes that were improved significantly as measured by patient report include goal setting, coordination of care, problem solving, and patient activation. In general, these effects were consistent among patients who rated their pre-study chronic care as “medium to high quality” and those who rated their pre-study chronic care as “low quality.”
Tools for evaluating the quality of chronic illness care for older adults with multi-morbidity are still under development and discussion. The limited applicability of disease-specific guidelines and tools for measuring the quality of health care for older adults with several chronic illnesses has been previously described4
. Patients with morbidity similar to those enrolled in this cRCT of GC are often excluded from the denominators of quality standards for specific diseases, thus excluding their care from measurement and, perhaps, from improvement17,18
. Yet, such multi-morbid patients experience the negative effects of a fragmented chronic care system at high rates, suggesting that evaluating their care with process measures not linked to specific diseases is especially important2,19,20
In this study, we employed the PACIC because it is a validated measure based on important elements of the CCM and because it is relevant to all chronically ill patients, regardless of their specific diagnoses and levels of co-morbidity. Higher PACIC scores indicate that elements of chronic care occur more often. The mean aggregate PACIC score at 18 months of 3.14 in the GC group indicates that, on average, goal setting, coordination of care, decision support, problem solving, and patient activation occurred “sometimes” to “most of the time.” The mean aggregate PACIC score of 2.85 in the UC group indicates that, on average, these elements “generally did not occur” or occurred “sometimes.” To our knowledge, however, no published research has established the magnitude of difference between mean PACIC scores that can be regarded with confidence as clinically significant. While higher levels of these elements of chronic care have been shown to be related to better health outcomes, it also remains unclear how frequently these elements must be provided to improve these outcomes. We currently do not have data to measure the association of perceived quality of care and other indicators of quality of care. Future analyses of GC insurance claims may provide some insight into this relationship.
To help quantify the effects of GC, we compared the proportions of the GC and UC groups that received elements of high-quality care “almost always” or “most of the time.” The resulting multiple logistic regression model suggests that recipients of GC had 2.13 times the odds as UC recipients to report high-quality care (Table ). Importantly, compared to the UC group, a significantly greater proportion of patients in the GC group who rated the quality of their care as “low” before the intervention reported a higher quality of care score 18 months later.
The GC model was designed to provide comprehensive, coordinated, patient-centered care. Possibly one of the most important components of this model is the accessibility of the nurse. A caseload of 50–60 patients allows the nurse to devote the time necessary to patients. As an example of this improved accessibility, GC patients were 70% more likely to rate the time they had to wait for an appointment when sick as “excellent” or “good” compared to usual care patients. Similarly, they were 50% more likely to rate the ability to get phone advice as “excellent” or “good.”
There are several limitations to the study. First, only 38% of the patients who were high-risk consented to participate. A portion of these patients opted out of the study initially, and others declined an in-home visit to provide consent when contacted by telephone. For privacy reasons, we were unable to collect any health or demographic information on people who refused to participate and who could not be located. It is likely that refusers had worse health than consenters, so the generalizability of the results reported here may be limited.
Second, the provision of GC to patients in one team within a practice could have “contaminated” the care provided to patients in the UC team within the practice. Although we saw no evidence that this occurred, it has the potential to reduce the measured differences between the GC and UC groups throughout the study. Theoretically, the unblinded design of the study also could have influenced the quality of the health care provided to the participants, although this is unlikely to have had a significant influence on the teams’ health-care processes.
The range in participants’ HCC risk ratios is the result of differences in the completeness with which practices entered diagnoses on their insurance claims. Less complete entry produced lower HCC risk ratios. In order to identify the patients with highest quartile of HCC risk ratios in practices where this was done, we had to include some patients with HCC ratios of less than 1.0. This may have led to the inclusion of some healthier people in our sample than we originally anticipated, among control and experimental participants.
We accepted proxies’ ratings of some participants’ quality of health care (5% at baseline, 11% at 18 months). Although the concordance between patients’ and proxies’ PACIC scores has not been reported, most of the proxies in this study were family caregivers who were well positioned to report the frequency with which the PACIC’s 20 elements of chronic care had occurred.
Our analyses assumed a common treatment effect across teams within each practice. While some teams may have implemented GC more effectively than others, this study was not powered to evaluate such heterogeneity. Strengths of this study include its enrollment of a large, diverse group of multi-morbid older adults who received care in different health-care delivery systems and were covered by three different health insurance plans, as well as its high rate of follow-up and its rigorous data collection and analytic methods.
In conclusion, these findings add support for the expanded use of GC to improve important elements of the quality of chronic health care for older people with multi-morbidity. Previously published papers have suggested that GC may produce short-term improvements in the quality of chronic care21
, reductions in family caregivers’ strain22
, and net cost savings for health insurers23
. Future work will study longer term health and cost outcomes.