Cost-Containment Strategies for Population Health Management and How They Relate to Poly Chronic Conditions

Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research

“…The challenges may include the development of valid and reliable measurement instruments for the KMAP, 1 the formulation and implementation of a long-term rather than a short-term observation period, 9,10 the avoidance of biases, 11 and the appropriate application of predictive analytics for teasing out the causal sequence of KMAP. 8 To facilitate more consistent preventive practice and better outcomes, it is imperative to understand causal mechanisms leading to behavioral changes and other patient care outcomes. 1…”

“…The future development of AI applications is highly feasible by employing the KMAP-O model to evaluate and monitor the efficacy on varying population types and distinguish between behavioral outcomes and overall clinical diabetes outcomes. A key premise with a population health management approach 8,21 is to help health managers perform risk stratification and identification of those “at-risk” for poor adherence and outcomes (i.e., a high-risk patient group). However, this approach has always over-generalized the effect of an intervention program for its therapeutic outcomes.…”

“…In the past decades, many clinical experimental studies pertaining to diabetes care were concerned with the main effects of multiple components of diabetes care intervention while only a few published articles considered the synergistic and interaction effects of KMAP on care outcomes. 4 The intervention studies were relatively heterogeneous in their design while diabetes education usually consisted of goal setting, knowledge acquisition, individualized care and frequent follow up. Most of these studies measured the short-term outcomes through monitoring patients’ adherence to medications, achieving lower HBA1C, improving dietary control behaviors, and weight loss.…”

“…In addition, targeting specific high-risk patients who experienced a poor adherence could yield better outcomes. 7,8 The complexity involved in designing a patient-centered care management for type 2 diabetes is also well documented. The challenges may include the development of valid and reliable measurement instruments for the KMAP, 1 the formulation and implementation of a long-term rather than a short-term observation period, 9,10 the avoidance of biases, 11 and the appropriate application of predictive analytics for teasing out the causal sequence of KMAP.…”

A Proposed Multi-Criteria Optimization Approach to Enhance Clinical Outcomes Evaluation for Diabetes Care: A Commentary

“…1,2 However, an optimal or ideal indicator of optimalization, using multi-criteria or multi-objectives approach, has yet to be introduced for enhancing the integrity of decisions or actions suggested by scientific evidence. Because health behaviors are part of social determinants of health, 2–4 it is imperative to search for an algorithm and identify relevant input and output components for reaching an appropriate mixture of predictor variables that will yield the balance of costs and benefits accrued from an intervention or a therapeutic mechanism.…”