Use of IndiGO individualized clinical guidelines in primary care

Primary care utilisation, adherence to guideline-based pharmacotherapy and continuity of care in primary care patients with chronic diseases and multimorbidity - a cross-sectional study

BACKGROUND

To understand how to improve care for patients with chronic diseases and multimorbidity we wanted to describe the prevalence of different chronic diseases and the pattern of multimorbidity and to analyse the associations between occurrence of diseases and primary care utilization, adherence to guideline-based pharmacotherapy, and continuity of care.

METHODS

Retrospective cross-sectional study of routine care data of the general population in region Jönköping in Sweden (345 916 inhabitants using primary care services) covering 4.3 years.

PARTICIPANTS

Patients fulfilling the inclusion criteria of having ≥ 1 of 10 common chronic diseases and ≥ 3 visits to primary care between 2011 and 2015.

PRIMARY OUTCOME MEASURES

In order to determine diseases and multimorbidity, primary care utilisation, adherence to guideline-based pharmacotherapy, frequencies and percentages, interval and ratio scaled variables were described using means, standard deviations, and various percentiles in the population. Two continuity indices were used (MMCI, COC) to describe continuity.

RESULTS

Of the general population, 25 829 patients fulfilled the inclusion criteria (7.5% of the population). Number of diseases increased with increasing age, and multimorbidity was much more common than single diseases (mean 2.0 per patient). There was a slight positive correlation (0.29) between number of diseases and visits, but visits did not increase proportionally to the number of diseases. Patients with physical diseases combined with anxiety and/or depression made more visits than others. The number of diseases per patient was negatively associated with the adherence to pharmacotherapy guidelines. There was no association between continuity and healthcare utilisation or adherence to pharmacotherapy guidelines.

CONCLUSIONS

Multimorbid patients are common in primary care and for many chronic diseases it is more common to have other simultaneous diseases than having only one disease. This can make adherence to pharmacotherapy guidelines a questionable measure for aged multimorbid patients. Existing continuity indices also revealed limitations. Holistic and patient-centred measures should be used for quality assessment of care for multimorbid patients in primary care.

Design, effectiveness, and economic outcomes of contemporary chronic disease clinical decision support systems: a systematic review and meta-analysis

Objectives

Electronic health record-based clinical decision support (CDS) has the potential to improve health outcomes. This systematic review investigates the design, effectiveness, and economic outcomes of CDS targeting several common chronic diseases.

Material and Methods

We conducted a search in PubMed (Medline), EBSCOHOST (CINAHL, APA PsychInfo, EconLit), and Web of Science. We limited the search to studies from 2011 to 2021. Studies were included if the CDS was electronic health record-based and targeted one or more of the following chronic diseases: cardiovascular disease, diabetes, chronic kidney disease, hypertension, and hypercholesterolemia. Studies with effectiveness or economic outcomes were considered for inclusion, and a meta-analysis was conducted.

Results

The review included 76 studies with effectiveness outcomes and 9 with economic outcomes. Of the effectiveness studies, 63% described a positive outcome that favored the CDS intervention group. However, meta-analysis demonstrated that effect sizes were heterogenous and small, with limited clinical and statistical significance. Of the economic studies, most full economic evaluations (n = 5) used a modeled analysis approach. Cost-effectiveness of CDS varied widely between studies, with an estimated incremental cost-effectiveness ratio ranging between USD$2192 to USD$151 955 per QALY.

Conclusion

We summarize contemporary chronic disease CDS designs and evaluation results. The effectiveness and cost-effectiveness results for CDS interventions are highly heterogeneous, likely due to differences in implementation context and evaluation methodology. Improved quality of reporting, particularly from modeled economic evaluations, would assist decision makers to better interpret and utilize results from these primary research studies.

Registration

PROSPERO (CRD42020203716)

Comprehensive process model of clinical information interaction in primary care: results of a "best-fit" framework synthesis

Objective

To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research.

Materials and Methods

We used the "best fit" framework synthesis approach. Searches were performed in PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Library and Information Science Abstracts, Library, Information Science and Technology Abstracts, and Engineering Village. Two authors reviewed articles according to inclusion and exclusion criteria. Data abstraction and content analysis of 443 published papers were used to create a model in which every element was supported by empirical research.

Results

The CIIM documents how primary care clinicians interact with information as they make point-of-care clinical decisions. The model highlights 3 major process components: (1) context, (2) activity (usual and contingent), and (3) influence. Usual activities include information processing, source-user interaction, information evaluation, selection of information, information use, clinical reasoning, and clinical decisions. Clinician characteristics, patient behaviors, and other professionals influence the process.

Discussion

The CIIM depicts the complete process of information interaction, enabling a grasp of relationships previously difficult to discern. The CIIM suggests potentially helpful functionality for clinical decision support systems (CDSSs) to support primary care, including a greater focus on information processing and use. The CIIM also documents the role of influence in clinical information interaction; influencers may affect the success of CDSS implementations.

Conclusion

The CIIM offers a new framework for achieving CDSS workflow integration and new directions for CDSS design that can support the work of diverse primary care clinicians.

Improving diabetes prevention with benefit based tailored treatment: risk based reanalysis of Diabetes Prevention Program

OBJECTIVE

To determine whether some participants in the Diabetes Prevention Program were more or less likely to benefit from metformin or a structured lifestyle modification program.

DESIGN

Post hoc analysis of the Diabetes Prevention Program, a randomized controlled trial.

SETTING

Ambulatory care patients.

PARTICIPANTS

3060 people without diabetes but with evidence of impaired glucose metabolism.

INTERVENTION

Intervention groups received metformin or a lifestyle modification program with the goals of weight loss and physical activity.

MAIN OUTCOME MEASURE

Development of diabetes, stratified by the risk of developing diabetes according to a diabetes risk prediction model.

RESULTS

Of the 3081 participants with impaired glucose metabolism at baseline, 655 (21%) progressed to diabetes over a median 2.8 years' follow-up. The diabetes risk model had good discrimination (C statistic=0.73) and calibration. Although the lifestyle intervention provided a sixfold greater absolute risk reduction in the highest risk quarter than in the lowest risk quarter, patients in the lowest risk quarter still received substantial benefit (three year absolute risk reduction 4.9% v 28.3% in highest risk quarter; numbers needed to treat of 20.4 and 3.5, respectively). The benefit of metformin, however, was seen almost entirely in patients in the top quarter of risk of diabetes. No benefit was seen in the lowest risk quarter. Participants in the highest risk quarter averaged a 21.4% three year absolute risk reduction (number needed to treat 4.6).

CONCLUSIONS

Patients at high risk of diabetes have substantial variation in their likelihood of receiving benefit from diabetes prevention treatments. Using this knowledge could decrease overtreatment and make prevention of diabetes far more efficient, effective, and patient centered, provided that decision making is based on an accurate risk prediction tool.