Table 4 Size effect and policy recommendations

Mateo Abad, 2020 [18]

The paper does not report specific effect sizes with confidence intervals. Still, it does indicate that the CareWell integrated care model was associated with reduced hospitalizations and emergency visits and increased primary care contacts.

The CareWell integrated care model should be considered when caring for complex, multimorbid older patients, as it led to a shift towards more primary care utilization, and fewer emergency and hospital visits.

Snooks, 2018 [17]

- Emergency hospital admission rates: 1% increase (95% CI 0.010 to 0.013)

- Emergency department attendance rates: 3% increase (95% CI 0.028 to 0.032)

- Outpatients visit rates: 5% increase (95% CI 0.051 to 0.058)

- Proportion of days with recorded GP activity: 1% increase (95% CI 0.007 to 0.014)

- Time in hospital: 3% increase (95% CI 0.026 to 0.031)

Policymakers should consider alternative approaches to managing high-risk patients, such as focusing on reducing length of hospital stay and preventing readmissions, rather than just identifying high-risk patients. Any interventions using predictive risk stratification tools should have explicit models of how they will work and undergo rigorous evaluation of their clinical and cost-effectiveness before implementation.

Lugo Palacios, 2019 [20]

The size effect for the primary outcome (emergency admissions for COPD, diabetes, and heart failure) was a non-significant increase of 7.6 admissions in the intervention site compared to the comparator (95% CI: − 3.7 to 19.0).

The authors recommend that national orchestrators of the NHS Test Beds scheme should: (1) Reconsider the emphasis on combinatorial innovation, as it may be contributing to implementation challenges. (2) Focus on spreading the individual components of the intervention, rather than the combinatorial approach. Specifically, the Evidence into Practice quality improvement component would be more difficult to spread to a larger area with the same resources.

Jiao 2015 [21]

For all-cause mortality, the hazard ratio was 0.363 (95% CI 0.308–0.428), indicating a 63.7% lower risk in the RAMP-DM group. For total CVD, the hazard ratio was 0.629 (95% CI 0.554–0.715), indicating a 37.1% lower risk in the RAMP-DM group compared to the control group. For CHD, the hazard ratio was 0.570 (95% CI 0.470–0.691), indicating a 43.0% lower risk in the RAMP-DM group.

Not applicable (the authors do not provide any explicit policy recommendations)

Wan 2018 [22]

After adjusting for baseline covariates, the RAMP-DM group had:

− 66.1% lower risk of all-cause mortality (HR 0.339, p < 0.001)

The authors recommend implementing a multidisciplinary, protocol-driven chronic disease model of care that involves risk stratification and early optimal diabetes control and risk factor management, in order to delay disease progression and prevent complications in patients with diabetes.

Gupta 2019 [23]

For patients with stage 4 or 5 chronic kidney disease (CKD), there was a nearly 2% reduction in monthly hospitalizations, with an IRR of 0.98 and a 95% confidence interval of 0.98–0.99 (p < 0.0001). For patients with dementia, there was a 1% monthly reduction in inpatient bed days, with an incident rate ratio (IRR) of 0.99 and a 95% confidence interval of 0.98–1.00 (p < 0.03).

Not mentioned (the paper does not contain any explicit policy recommendations)

Soto-Gordoa 2019 [19]

For prioritized patients:

- Increase in probability of outpatient visists (OR: 2.10, CI: 1.70–2.39)

- Increase in number of primary care contacts (OR: 1.07, CI: 1.05–1.10)

- Decrease in probability of hospitalization (OR: 0.91, CI: 0.86–0.96)

- Decrease in number of hospitalizations (OR: 0.96, CI: 0.91–1.00)

For non-prioritized patients:

- Increase in probability of outpatient visits (OR: 1.64, CI: 1.27–2.39)

- Decrease in number of primary care contacts (OR: 0.95, CI: 0.92–0.97)

- Increase in probability of hospitalization (OR: 1.19, CI: 1.09–1.30)

Based on the study, the key policy recommendations are:

1. Prioritize integrated care interventions on specific populations most likely to benefit, rather than broad populations.

2. Carefully select the target population for integrated care programs to maximize their effectiveness.

3. Utilize observational study designs that capture real-world healthcare contexts, in addition to randomized trials, to evaluate the impact of interventions.

4. Leverage electronic health records and appropriate statistical methods to improve the validity of results when assessing healthcare interventions.