Citations

The industrialisation of healthcare has transformed the expectation of individualised and compassionate caring for patients into the reality of efficient and standardised processing of people to achieve organisational goals. In this way, healthcare functions like a machine that processes patients via protocols and technologies. Though this standardisation is necessary for enhancing safe and efficient operations, it can also alienate organisations and their clinicians from their core mission, turning care into a transactional endeavour. Consequently, patients must adapt to the system’s needs and work to achieve its goals, adding unnecessary burden and limiting the benefits of their healing endeavour. In this opinion piece, the authors offer an alternative vision of care as the work of people who, in interaction, notice and respond to each patient’s problematic human situation. Healthcare organisations must reclaim this care as its core mission, and foster environments where patients and clinicians may engage in this adaptative and responsive practice. By doing so, healthcare can fulfil its purpose: to care for all in a way that is careful and kind.

Abstract Background Patients living with diabetes and chronic conditions may face significant burden managing their health. Many of these patients use digital medicine tools such as continuous glucose monitoring systems. Although measures exist to assess treatment burden from tasks such as managing medications and attending healthcare visits, there is no patient-reported measure that captures the burden of digital care. Therefore, the purpose of this study is to validate the Treatment Burden Questionnaire Plus Digital (TBQ + D), a patient-reported measure of treatment burden that includes using digital tools for adults with diabetes. Methods Adult patients with type 1 or type 2 diabetes mellitus completed the 25-item TBQ + D (scored 0 [none] to 10 [maximum] per item; total score range 0–250). We evaluated ease of administration, internal consistency, and tested hypotheses about the relationship between TBQ + D scores and treatment complexity, digital tool use intensity, social risk factors, and digital comfort to assess TBQ + D’s validity. Results Of 324 patients approached, 300 (93%) consented and completed the TBQ + D (mean age 57 [SD 17]; 50% female; 50% with type 2). The mean TBQ + D score was 53.7 (SD 41.6). Internal consistency was excellent (Cronbach’s α = 0.94). As hypothesized, higher TBQ + D scores were reported by patients with type 1 vs. type 2 diabetes mellitus (61.7 vs. 45.7; p = .0008), maximal/moderate vs. minimal to no digital tool use (56.5/60.7 vs. 41.3; p = .001), those on intensive insulin therapy vs. other treatments (61.4 vs. 38.0; p < .0001), and those with greater social vulnerability (p < .0106). TBQ + D scores were not significantly higher in patients with HbA1c ≥ 8% (p = .055) or less comfortable with digital technology (p = .08). Conclusions TBQ + D is a novel and valid measure of treatment burden in patients living with diabetes, inclusive of digital burden, that can play a role in fostering minimally disruptive care for patients with diabetes.

Background Statin Choice is a shared decision-making encounter tool embedded in the electronic health record. Objective To describe the association between the use of Statin Choice, statin prescriptions by clinicians, prescription fills (primary adherence), and statin adherence at 12 mo (secondary adherence). Design Observational cohort study at the Cleveland Clinic Health System. Subjects Statin-naïve adults aged 40 to 75 y with a 10-y atherosclerotic cardiovascular disease (ASCVD) risk of ≥5% and a primary care appointment between January 2020 and July 2021. Main Measures The primary exposure was the use of Statin Choice during a clinical encounter. We measured whether the use of Statin Choice was associated with statin prescriptions. We measured statin adherence based on pharmacy fill data at 60 d (primary adherence) and 12 mo (secondary adherence). We used mixed-effects logistic regression to estimate the adjusted odds of statin prescriptions and adherence at the 3 time points by the use of Statin Choice. Key Results Among 17,001 statin-naïve patients, 13% viewed Statin Choice and 7% were prescribed a statin. The median ASCVD risk was 10%. Patients who were shown Statin Choice had 9.04 higher odds of being prescribed a statin compared with patients not shown Statin Choice (95% confidence interval [CI]: 7.86–10.4). Among patients prescribed a statin, the use of Statin Choice was associated with 5.75 higher odds of primary adherence compared with usual care (95% CI: 4.22–7.83). At 12 mo, Statin Choice use was significantly associated with adherence in the unadjusted analysis (OR: 1.58; 95% CI: 1.05–2.08) but was not significant after adjustment for patient factors. Patients shown Statin Choice had an average of 12 mg/dL reduction in low-density lipoprotein cholesterol at 12 mo (95% CI: −16 mg/dL, −10) compared with those not shown Statin Choice. Conclusion In this observational study, Statin Choice use was strongly associated with statin prescription and fills and weakly associated with adherence to statins for up to 1 y. A randomized trial is needed to confirm causality. Highlights Statin Choice is an electronic health record–embedded shared decision-making encounter tool available for free in many health care systems. Small randomized controlled trials have found modest associations between the use of Statin Choice and statin adherence using patient-reported data. In our large study using pharmacy fill data, clinician use of Statin Choice during a medical encounter was associated with significantly greater patient adherence with statins up to 1 y later. Exposure to Statin Choice was associated with a significant reduction in low-density lipoprotein cholesterol over 1 y.