Workflow standardization of a novel team care model to improve chronic care: a quasi-experimental study.

BACKGROUND: Team-based chronic care models have not been widely adopted in community settings, partly due to their varying effectiveness in randomized control trials, implementation challenges, and concerns about physician acceptance. The Palo Alto Medical Foundation designed and implemented "Champion," a novel team-based model that includes new standard work (e.g. proactive patient outreach, pre-visit schedule grooming, depression screening, care planning, health coaching) to support patients' self-management of hypertension and diabetes. We investigated whether Champion improved clinical outcomes. METHODS: We conducted a quasi-experimental study comparing the Champion clinic-level intervention (n = 38 physicians) with a usual care clinic (n = 37 physicians) in Northern California. The primary outcomes, blood pressure and glycohemoglobin (A1c), were analyzed using a piecewise linear growth curve model for patients exposed to a Champion physician visit (n = 3156) or usual care visit (n = 8034) in the two years prior and one year post implementation. Secondary outcomes were provider experience, compared at baseline and 12 months in both the intervention and usual care clinics using multi-level ordered logistic modeling, and electronic health record based fidelity measures. RESULTS: Compared to usual care, in the first 6 months after a Champion physician visit, diabetes patients aged 18-75 experienced an additional -1.13 mm Hg (95% CI: -2.23 to -0.04) decline in diastolic blood pressure and -0.47 (95% CI: -0.61 to -0.33) decline in A1c. There were no additional improvements in blood pressure or A1c 6 to 12 months post physician visit. At 12 months, Champion physicians reported improved experience with managing chronic care patients in 6 of 7 survey items (p < 0.05), but compared to usual, this difference was only statistically significant for one item (p < 0.05). Fidelity to standard work was uneven; depression screening was the most commonly documented element (85% of patients), while care plans were the least (30.8% of patients). CONCLUSIONS: Champion standard work improved glycemic control over the first 6 months and physicians' experience with managing chronic care; changes in blood pressure were not clinically meaningful. Our results suggest the need to understand the relationship between the intervention, the contextual features of implementation, and fidelity to further improve chronic disease outcomes. This study was retrospectively registered with the ISRCTN Registry on March 15, 2017 (ISRCTN11341906).

Patients' body mass index and blood pressure over time: diagnoses, treatments, and the effects of comorbidities.

BACKGROUND: A national strategic framework to address multiple chronic conditions has called for further research on disease trajectories of patients with comorbidities. METHODS: An observational study using multilevel models to analyze electronic health record data from a multispecialty practice from 2003 to 2010 to examine disease trajectories of patients with at least 2 of 3 common chronic conditions: overweight/obese, hypertension, and depression. Using longitudinal data on up to 110,000 patients, the effects of comorbidities on the probability of having a diagnosis for overweight/obesity or hypertension and on the trajectories of body mass index (BMI) and blood pressure (BP) over time were examined. RESULTS: From 2003 to 2010, the percentage of patients with high BMI receiving an overweight/obesity diagnosis grew from 5.0% to 18.7%, and the percentage of patients with high BP having a hypertension diagnosis rose from 39.9% to 51.7%. The effect of time for patients with high BMI and depression was less than the effect of time for high BMI only patients (P<0.01) in receiving overweight/obesity diagnoses. Co-occurring depression and high BMI was positively associated with BMI trajectory (coefficient=0.06, P<0.01), whereas high BP and high BMI (coefficient=-0.07, P<0.01) or high BP and high BMI and depression (coefficient=-0.05, P<0.01) were negatively associated with BMI trajectories. CONCLUSIONS: Although physicians' recording of diagnoses for patients with high BMI and high BP has improved, significant gaps remain. Some co-occurrence patterns of these 3 conditions not only affected the recognition of overweight/obesity and hypertension over time, but also BMI trajectories over time. Quality improvement efforts should target patients with co-occurring depression and overweight/obesity.

Cost Estimates for Designing and Implementing a Novel Team Care Model for Chronically Ill Patients.

Little is known about the cost of implementing chronic care models. We estimate the human resource cost of implementing a novel team-based chronic care model "Champion," at a large multispecialty group practice. We used activity-based costing to calculate costs from development through rollout and stabilization in 1 clinic with 12 000 chronic care patients. Data analyzed included Microsoft Outlook meeting metadata, supporting documents, and 2014 employee wages. Implementation took more than 29 months, involved 168 employees, and cost the organization $2 304 787. Payers may need to consider a mixed-payment model to support the both implementation and maintenance costs of team-based chronic care.

Electronic Health Record Logs Indicate That Physicians Split Time Evenly Between Seeing Patients And Desktop Medicine.

Time spent by physicians is a key resource in health care delivery. This study used data captured by the access time stamp functionality of an electronic health record (EHR) to examine physician work effort. This is a potentially powerful, yet unobtrusive, way to study physicians' use of time. We used data on physicians' time allocation patterns captured by over thirty-one million EHR transactions in the period 2011-14 recorded by 471 primary care physicians, who collectively worked on 765,129 patients' EHRs. Our results suggest that the physicians logged an average of 3.08 hours on office visits and 3.17 hours on desktop medicine each day. Desktop medicine consists of activities such as communicating with patients through a secure patient portal, responding to patients' online requests for prescription refills or medical advice, ordering tests, sending staff messages, and reviewing test results. Over time, log records from physicians showed a decline in the time allocated to face-to-face visits, accompanied by an increase in time allocated to desktop medicine. Staffing and scheduling in the physician's office, as well as provider payment models for primary care practice, should account for these desktop medicine efforts.