The quality of care among older adults with diabetes comorbid with other chronic conditions

The management of people with multiple chronic conditions requires understanding the extent to which concurrent chronic conditions contribute and interact to affect the patientâ s health status, as well as assessing the risk and benefits of various strategies for the treatment of complex needs in patients. A single condition focus in both clinical care and research remains and limits the assessment of care for people with multiple chronic conditions. The overall aim of this project was to evaluate the quality of overall care for older adults with selected disease combinations in ambulatory care settings. The first study aimed to identify a set of evidence-based and valid quality indicators for evaluating ambulatory care for older adults with selected chronic conditions, including diabetes, hypertension, chronic ischemic heart disease, major depression and osteoarthritis. The second study aimed to critically appraise the identified quality indicators and select a set of indicators for evaluating the quality of care for older adults with diabetes with comorbid concordant and discordant chronic conditions. The third study aimed to examine the difference in the quality of care between patients with 2 vs. 1 selected concordant vs. discordant comorbid conditions, and to examine associations of quality of care and hospitalizations among older adults with selected disease combinations. The study findings suggest that older adults with diabetes are at risk of suboptimal care with additional selected comorbid conditions, especially those with discordant comorbid conditions. The study findings also support the importance of continuity of care for older diabetes patients with comorbid chronic conditions. The study findings suggest that the likelihood of hospitalizations increases with the number of prescribed drugs among older adults with comorbidities. There is a need for a holistic approach in education and clinical care of older adults with diabetes taking into account concomitant conditions that affect patientâ s health status. Future research is needed for measuring the quality of care in the larger diabetes population and reporting by different stratifications, including age, sex, primary care models to see if there are any patterns in certain groups and target the interventions towards improving practices for specific sub groups.Ph.D

Quality indicators for ambulatory care for older adults with diabetes and comorbid conditions: A Delphi study.

BACKGROUND:An increasing number of people are living with multiple chronic conditions and it is unclear which quality indicators should be used to guide care for this population. OBJECTIVE:To critically appraise and select the most appropriate set of quality indicators for ambulatory care for older adults with five selected disease combinations. METHODS:A two-round web-based Delphi process was used to critically appraise and select quality of care indicators for older adults with diabetes and comorbidities. A fifteen-member Canadian expert panel with broad geographical and clinical representation participated in this study. The panel evaluated process indicators for meaningfulness, potential for improvements in clinical practice, and overall value of inclusion, while outcome indicators were evaluated for importance, modifiability and overall value of inclusion. A 70% agreement threshold was required for high consensus, and 60-69% for moderate consensus as measured on a 5-point Likert type scale. RESULTS:Twenty high-consensus and nineteen medium-consensus process and outcome indicators were selected for assessing care for older adults with selected disease combinations, including 1) concordant (conditions with a common management plan), 2) discordant (conditions with unrelated management plans), and 3) both types. Panelists reached rapid consensus on quality indicators for care for older adults with concordant comorbid conditions, but not for those with discordant conditions. All selected indicators assess clinical aspects of care. The feedback from the panelists emphasized the importance of developing indicators related to patient-centred aspects of care, including patient self-management, education, patient-physician relationships, and patient's preferences. CONCLUSIONS:The selected quality indicators are not intended to provide a comprehensive tool set for measuring quality of care for older adults with selected disease combinations. The recommended indicators address clinical aspects of care and can be used as a starting point for ambulatory care settings and development of additional quality indicators

Quality indicators for care of depression in primary care settings: a systematic review

Abstract Background Despite the growing interest in assessing the quality of care for depression, there is little evidence to support measurement of the quality of primary care for depression. This study identified evidence-based quality indicators for monitoring, evaluating and improving the quality of care for depression in primary care settings. Methods Ovid MEDLINE and Ovid PsycINFO databases, and grey literature, including relevant organizational websites, were searched from 2000 to 2015. Two reviewers independently selected studies if (1) the study methodology combined a systematic literature search with assessment of quality indicators by an expert panel and (2) quality indicators were applicable to assessment of care for adults with depression in primary care settings. Included studies were appraised using the Appraisal of Indicators through Research and Evaluation (AIRE) instrument, which contains four domains and 20 items. A narrative synthesis was used to combine the indicators within themes. Quality indicators applicable to care for adults with depression in primary care settings were extracted using a structured form. The extracted quality indicators were categorized according to Donabedian’s ‘structure-process-outcome’ framework. Results The search revealed 3838 studies. Four additional publications were identified through grey literature searching. Thirty-nine articles were reviewed in detail and seven met the inclusion criteria. According to the AIRE domains, all studies were clear on purpose and stakeholder involvement, while formal endorsement and usage of indicators in practice were scarcely described. A total of 53 quality indicators were identified from the included studies, many of which overlap conceptually or in content: 15 structure, 33 process and four outcome indicators. This study identified quality indicators for evaluating primary care for depression among adult patients. Conclusions The identified set of indicators address multiple dimensions of depression care and provide an excellent starting point for further development and use in primary care settings

Predicting postoperative surgical site infection with administrative data: a random forests algorithm

Background Since primary data collection can be time-consuming and expensive, surgical site infections (SSIs) could ideally be monitored using routinely collected administrative data. We derived and internally validated efficient algorithms to identify SSIs within 30 days after surgery with health administrative data, using Machine Learning algorithms. Methods All patients enrolled in the National Surgical Quality Improvement Program from the Ottawa Hospital were linked to administrative datasets in Ontario, Canada. Machine Learning approaches, including a Random Forests algorithm and the high-performance logistic regression, were used to derive parsimonious models to predict SSI status. Finally, a risk score methodology was used to transform the final models into the risk score system. The SSI risk models were validated in the validation datasets. Results Of 14,351 patients, 795 (5.5%) had an SSI. First, separate predictive models were built for three distinct administrative datasets. The final model, including hospitalization diagnostic, physician diagnostic and procedure codes, demonstrated excellent discrimination (C statistics, 0.91, 95% CI, 0.90–0.92) and calibration (Hosmer-Lemeshow χ2 statistics, 4.531, p = 0.402). Conclusion We demonstrated that health administrative data can be effectively used to identify SSIs. Machine learning algorithms have shown a high degree of accuracy in predicting postoperative SSIs and can integrate and utilize a large amount of administrative data. External validation of this model is required before it can be routinely used to identify SSIs.Medicine, Faculty ofNon UBCAnesthesiology, Pharmacology and Therapeutics, Department ofReviewedFacultyResearche

Additional file 3: of Quality indicators for care of depression in primary care settings: a systematic review

PRISMA checklist. (PDF 176 kb

A multi-level qualitative analysis of Telehomecare in Ontario: challenges and opportunities

Abstract Background Despite research demonstrating the potential effectiveness of Telehomecare for people with Chronic Obstructive Pulmonary Disease and Heart Failure, broad-scale comprehensive evaluations are lacking. This article discusses the qualitative component of a mixed-method program evaluation of Telehomecare in Ontario, Canada. The objective of the qualitative component was to explore the multi-level factors and processes which facilitate or impede the implementation and adoption of the program across three regions where it was first implemented. Methods The study employs a multi-level framework as a conceptual guide to explore the facilitators and barriers to Telehomecare implementation and adoption across five levels: technology, patients, providers, organizations, and structures. In-depth semi-structured interviews and ethnographic observations with program stakeholders, as well as a Telehomecare document review were used to elicit key themes. Study participants (n = 89) included patients and/or informal caregivers (n = 39), health care providers (n = 23), technicians (n = 2), administrators (n = 12), and decision makers (n = 13) across three different Local Health Integration Networks in Ontario. Results Key facilitators to Telehomecare implementation and adoption at each level of the multi-level framework included: user-friendliness of Telehomecare technology, patient motivation to participate in the program, support for Telehomecare providers, the integration of Telehomecare into broader health service provision, and comprehensive program evaluation. Key barriers included: access-related issues to using the technology, patient language (if not English or French), Telehomecare provider time limitations, gaps in health care provision for patients, and structural barriers to patient participation related to geography and social location. Conclusions Though Telehomecare has the potential to positively impact patient lives and strengthen models of health care provision, a number of key challenges remain. As such, further implementation and expansion of Telehomecare must involve continuous assessments of what is working and not working with all stakeholders. Increased dialogue, evaluation, and knowledge translation within and across regions to understand the contextual factors influencing Telehomecare implementation and adoption is required. This can inform decision-making that better reflects and addresses the needs of all program stakeholders

The association between multimorbidity and hospitalization is modified by individual demographics and physician continuity of care: a retrospective cohort study

Abstract Background Multimorbidity poses a significant clinical challenge and has been linked to greater health services use, including hospitalization; however, we have little knowledge about the influence of contextual factors on outcomes in this population. Objectives: To describe the extent to which the association between multimorbidity and hospitalization is modified by age, gender, primary care practice model, or continuity of care (COC) among adults with at least one chronic condition. Methods A retrospective cohort study with linked population-based administrative data. Setting: Ontario, Canada. Cohort: All individuals 18 and older with at least one of 16 priority chronic conditions as of April 1, 2009 (baseline). Main Outcome Measures: Any hospitalization, 3 or more hospitalizations, non-medical discharge delay, and 30-day readmission within the 1 year following baseline. Results Of 5,958,514 individuals, 484,872 (8.1 %) experienced 646,347 hospitalizations. There was a monotonic increase in the likelihood of hospitalization and related outcomes with increasing multimorbidity which was modified by age, gender, and COC but not primary care practice model. The effect of increasing multimorbidity was greater in younger adults than older adults and in those with lower COC than with higher COC. The effect of increasing multimorbidity on hospitalization was greater in men than women but reversed for the other outcomes. Conclusions The effect of multimorbidity on hospitalization is influenced by age and gender, important considerations in the development of person-centred care models. Greater continuity of physician care lessened the effect of multimorbidity on hospitalization, further demonstrating the need for care continuity across providers for people with chronic conditions

The increasing burden and complexity of multimorbidity

Abstract Background Multimorbidity, the co-occurrence of two or more chronic conditions, is common among older adults and is known to be associated with high costs and gaps in quality of care. Population-based estimates of multimorbidity are not readily available, which makes future planning a challenge. We aimed to estimate the population-based prevalence and trends of multimorbidity in Ontario, Canada and to examine patterns in the co-occurrence of chronic conditions. Methods This retrospective cohort study includes all Ontarians (aged 0 to 105 years) with at least one of 16 common chronic conditions. Descriptive statistics were used to examine and compare the prevalence of multimorbidity by age and number of conditions in 2003 and 2009. The co-occurrence of chronic conditions among individuals with multimorbidity was also explored. Results The prevalence of multimorbidity among Ontarians rose from 17.4% in 2003 to 24.3% in 2009, a 40% increase. This increase over time was evident across all age groups. Within individual chronic conditions, multimorbidity rates ranged from 44% to 99%. Remarkably, there were no dominant patterns of co-occurring conditions. Conclusion The high prevalence of multimorbidity and numerous combinations of conditions suggests that single, disease-oriented management programs may be less effective or efficient tools for high quality care compared to person-centered approaches

Additional file 1: of A multi-level qualitative analysis of Telehomecare in Ontario: challenges and opportunities

Semi-structured interview guides. (PDF 409 kb