Quality Indicator Rates for Seriously Ill Home Care Clients: Analysis of Resident Assessment Instrument for Home Care Data in Six Canadian Provinces

Update on Prevalence of Pain in Patients with Cancer 2022: A Systematic Literature Review and Meta-Analysis

Experiencing pain and insufficient relief can be devastating and negatively affect a patient's quality of life. Developments in oncology such as new treatments and adjusted pain management guidelines may have influenced the prevalence of cancer pain and severity in patients. This review aims to provide an overview of the prevalence and severity of pain in cancer patients in the 2014-2021 literature period. A systematic literature search was performed using the databases PubMed, Embase, CINAHL, and Cochrane. Titles and abstracts were screened, and full texts were evaluated and assessed on methodological quality. A meta-analysis was performed on the pooled prevalence and severity rates. A meta-regression analysis was used to explore differences between treatment groups. We identified 10,637 studies, of which 444 studies were included. The overall prevalence of pain was 44.5%. Moderate to severe pain was experienced by 30.6% of the patients, a lower proportion compared to previous research. Pain experienced by cancer survivors was significantly lower compared to most treatment groups. Our results imply that both the prevalence of pain and pain severity declined in the past decade. Increased attention to the assessment and management of pain might have fostered the decline in the prevalence and severity of pain.

A multi-stage process to develop quality indicators for community-based palliative care using interRAI data

Background

Individuals receiving palliative care (PC) are generally thought to prefer to receive care and die in their homes, yet little research has assessed the quality of home- and community-based PC. This project developed a set of valid and reliable quality indicators (QIs) that can be generated using data that are already gathered with interRAI assessments—an internationally validated set of tools commonly used in North America for home care clients. The QIs can serve as decision-support measures to assist providers and decision makers in delivering optimal care to individuals and their families.

Methods

The development efforts took part in multiple stages, between 2017–2021, including a workshop with clinicians and decision-makers working in PC, qualitative interviews with individuals receiving PC, families and decision makers and a modified Delphi panel, based on the RAND/ULCA appropriateness method.

Results

Based on the workshop results, and qualitative interviews, a set of 27 candidate QIs were defined. They capture issues such as caregiver burden, pain, breathlessness, falls, constipation, nausea/vomiting and loneliness. These QIs were further evaluated by clinicians/decision makers working in PC, through the modified Delphi panel, and five were removed from further consideration, resulting in 22 QIs.

Conclusions

Through in-depth and multiple-stakeholder consultations we developed a set of QIs generated with data already collected with interRAI assessments. These indicators provide a feasible basis for quality benchmarking and improvement systems for care providers aiming to optimize PC to individuals and their families.

Mood Disturbances Across the Continuum of Care Based on Self-Report and Clinician Rated Measures in the interRAI Suite of Assessment Instruments

BACKGROUND

Mood disturbance is a pervasive problem affecting persons of all ages in the general population and the subset of those receiving services from different health care providers. interRAI assessment instruments comprise an integrated health information system providing a common approach to comprehensive assessment of the strengths, preferences and needs of persons with complex needs across the continuum of care.

OBJECTIVE

Our objective was to create new mood scales for use with the full suite of interRAI assessments including a composite version with both clinician-rated and self-reported items as well as a self-report only version.

METHODS

We completed a cross-sectional analysis of 511,641 interRAI assessments of Canadian adults aged 18+ in community mental health, home care, community support services, nursing homes, palliative care, acute hospital, and general population surveys to develop, test, and refine new measures of mood disturbance that combined clinician and self-rated items. We examined validity and internal consistency across diverse care settings and populations.

RESULTS

The composite scale combining both clinician and self-report ratings and the self-report only variant showed different distributions across populations and settings with most severe signs of disturbed mood in community mental health settings and lowest severity in the general population prior to the COVID-19 pandemic. The self-report and composite measures were strongly correlated with each other but differed most in populations with high rates of missing values for self-report due to cognitive impairment (e.g., nursing homes). Evidence of reliability was strong across care settings, as was convergent validity with respect to depression/mood disorder diagnoses, sleep disturbance, and self-harm indicators. In a general population survey, the correlation of the self-reported mood scale with Kessler-10 was 0.73.

CONCLUSIONS

The new interRAI mood scales provide reliable and valid mental health measures that can be applied across diverse populations and care settings. Incorporating a person-centered approach to assessment, the composite scale considers the person's perspective and clinician views to provide a sensitive and robust measure that considers mood disturbances related to dysphoria, anxiety, and anhedonia.

Quality indicators for dementia and older people nearing the end of life: A systematic review

BACKGROUND

Robust quality indicators (QIs) are essential for monitoring and improving the quality of care and learning from good practice. We aimed to identify and assess QIs for the care of older people and people with dementia who are nearing the end of life and recommend QIs for use with routinely collected electronic data across care settings.

METHODS

A systematic review was conducted, including five databases and reference chaining. Studies describing the development of QIs for care of older people and those with dementia nearing the end of life were included. QIs were categorized as relating to processes or outcomes, and mapped against six care domains. The psychometric properties (acceptability, evidence base, definition, feasibility, reliability, and validity) of each QI were assessed; QIs were categorized as robust, moderate, or poor.

RESULTS

From 12,980 titles and abstracts screened, 37 papers and 976 QIs were included. Process and outcome QIs accounted for 780 (79.7%) and 196 (20.3%) of all QIs, respectively. Many of the QIs concerned physical aspects of care (n = 492, 50.4%), and very few concerned spiritual and cultural aspects of care (n = 19, 1.9%). Three hundred and fifteen (32.3%) QIs were robust and of those 220 were measurable using routinely collected electronic data. The final shortlist of 71 QIs came from seven studies.

CONCLUSIONS

Of the numerous QIs developed for care of older adults and those with dementia nearing the end of life, most had poor or moderate psychometric properties or were not designed for use with routinely collected electronic datasets. Infrastructure for data availability, combined with use of robust QIs, is important for enhancing understanding of care provided to this population, identifying unmet needs, and improving service provision.

Trajectory of psychosocial symptoms among home care patients with cancer at end-of-life

PURPOSE

Understanding the end-of-life psychosocial needs of cancer patients at home is a knowledge gap. This study describes the trajectory of psychosocial symptoms in the last 6 months of life among cancer decedents who were receiving home care.

METHODS

Observational population-based cohort study of cancer decedents who were receiving home care services between 2007 and 2014. Decedents had to have at least one home care assessment in the last 6 months of life for inclusion. Outcomes were the presence of psychosocial symptoms (i.e., anxiety, loneliness, depression, social decline, caregiver distress, and cognitive decline) at each week before death.

RESULTS

Our cohort included 27,295 unique cancer decedents (30,368 assessments), of which 58% died in hospital. Fifty-six percent were older than 74, and 47% were female. The prevalence of all symptoms increased approaching death, except loneliness. Social decline (48%-78%) was the most prevalent psychosocial symptom, though loneliness was reported in less than 10% of the cohort. Caregiver distress rose over time from 15%-27%. A third of the cohort reported issues with cognitive impairment. Multivariate regression showed that physical symptoms such as uncontrolled pain, impairment in independent activities of daily living, and a high level of health instability all significantly worsened the odds of having a psychosocial symptom in the last 3 months of life.

CONCLUSION

In this large home care cancer cohort, trajectories of psychosocial symptoms worsened close to death. Physical symptoms, such as uncontrolled pain, were associated with having worse psychosocial symptoms at end of life.

Development of comparable algorithms to measure primary care indicators using administrative health data across three Canadian provinces

INTRODUCTION

Performance measurement has been recognized as key to transforming primary care (PC). Yet, performance reporting in PC lags behind even though high-performing PC is foundational to an effective and efficient health care system.

OBJECTIVES

We used administrative data from three Canadian provinces, British Columbia, Ontario and Nova Scotia, to: 1) identify and develop a core set of PC performance indicators using administrative data and 2) examine their ability to capture PC performance.

METHODS

Administrative data used included Physician Billings, Discharge Abstract Database, the National Ambulatory Care and Reporting System database, Census and Vital Statistics. Indicators were compiled based on a literature review of PC indicators previously developed with administrative data available in Canada (n=158). We engaged in iterative discussions to assess data conformity, completeness, and plausibility of results in all jurisdictions. Challenges to creating comparable algorithms were examined through content analysis and research team discussions, which included clinicians, analysts, and health services researchers familiar with PC.

RESULTS

Our final list included 21 PC performance indicators pertaining to 1) technical care (n=4), 2) continuity of care (n=6), and 3) health services utilization (n=11). Establishing comparable algorithms across provinces was possible though time intensive. A major challenge was inconsistent data elements. Ease of data access, and a deep understanding of the data and practice context, was essential for selecting the most appropriate data elements.

CONCLUSIONS

This project is unique in creating algorithms to measure PC performance across provinces. It was essential to balance internal validity of the indicators within a province and external validity across provinces. The intuitive desire of having the exact same coding across provinces was infeasible due to lack of standardized PC data. Rather, a context-tailored definition was developed for each jurisdiction. This work serves as an example for developing comparable PC performance indicators across different provincial/territorial jurisdictions.

Development and Validation of a Prognostic Survival Model With Patient-Reported Outcomes for Patients With Cancer

IMPORTANCE

Existing prognostic cancer tools include biological and laboratory variables. However, patients often do not know this information, preventing them from using the tools and understanding their prognosis.

OBJECTIVE

To develop and validate a prognostic survival model for all cancer types that incorporates information on symptoms and performance status over time.

DESIGN, SETTING, AND PARTICIPANTS

This is a retrospective, population-based, prognostic study of data from patients diagnosed with cancer from January 1, 2008, to December 31, 2015, in Ontario, Canada. Patients were randomly selected for model derivation (60%) and validation (40%). The derivation cohort was used to develop a multivariable Cox proportional hazards regression model with baseline characteristics under a backward stepwise variable selection process to predict the risk of mortality as a function of time. Covariates included demographic characteristics, clinical information, symptoms and performance status, and health care use. Model performance was assessed on the validation cohort by C statistics and calibration plots. Data analysis was performed from February 6, 2018, to November 6, 2019.

MAIN OUTCOMES AND MEASURES

Time to death from diagnosis (year 0) recalculated at each of 4 annual survivor marks after diagnosis (up to year 4).

RESULTS

A total of 255 494 patients diagnosed with cancer were identified (135 699 [53.1%] female; median age, 65 years [interquartile range, 55-73 years]). The cohort decreased to 217 055, 184 822, 143 649, and 109 569 patients for each of the 4 years after diagnosis. In the derivation cohort year 0, and the most common cancers were breast (30 855 [20.1%]), lung (19 111 [12.5%]), and prostate (18 404 [12.0%]). A total of 47 614 (31.1%) had stage III or IV disease. The mean (SD) time to death in year 0 was 567 (715) days. After backward stepwise selection in year 0, the following factors were associated with increased risk of death by more than 10%: being hospitalized; having congestive heart failure, chronic obstructive pulmonary disease, or dementia; having moderate to high pain; having worse well-being; having functional status in the transitional or end-of-life phase; having any problems with appetite; receiving end-of-life home care; and living in a nursing home. Model discrimination was high for all models (C statistic: 0.902 [year 0], 0.912 [year 1], 0.912 [year 2], 0.909 [year 3], and 0.908 [year 4]).

CONCLUSIONS AND RELEVANCE

The model accurately predicted changing cancer survival risk over time using clinical, symptom, and performance status data and appears to have the potential to be a useful prognostic tool that can be completed by patients. This knowledge may support earlier integration of palliative care.

Associations with rates of falls among home care clients in Ontario, Canada: a population-based, cross-sectional study

BACKGROUND

Accidental falls among older adults are a leading cause of injury-related hospitalizations. Reducing falls is an ongoing quality improvement priority for home care, given that many home care clients experience falls. In this study, we identify factors associated with the rate of falls among home care clients.

METHODS

We conducted a population-based, cross-sectional study using secondary data from the Hamilton, Niagara, Haldimand, and Brant health region of Ontario, Canada from January 1 - March 31, 2018. We captured person-level characteristics with falls from the Resident Assessment Instrument - Home Care (RAI-HC). Negative binomial regression was used to model the rate of falls.

RESULTS

Functional characteristics of home care clients had strong, statistically significant associations with the rate of falls. Declines in activities of daily living, assistive device use for locomotion indoors, polypharmacy, and health conditions, such as dizziness or lightheadedness, and parkinsonism, were associated with a higher rate of falls. Males who used assistive devices had a higher rate of falls compared to females; however, males with neurological and cardiovascular health conditions had a decrease in the rate of falls compared to females. Home care clients with parkinsonism who used a cane and took eight or more drugs had stronger associations with an increased rate of falls compared to those who do not have parkinsonism.

CONCLUSIONS

Functional characteristics, polypharmacy, and health conditions are associated with increased rates of falls among home care clients. Home care clients who are at a greater risk of falls may require environmental adjustments in their home to reduce or eliminate the possibility of falling.

The interRAI Suite of Mental Health Assessment Instruments: An Integrated System for the Continuum of Care

The lives of persons living with mental illness are affected by psychological, biological, social, economic, and environmental factors over the life course. It is therefore unlikely that simple preventive strategies, clinical treatments, therapeutic interventions, or policy options will succeed as singular solutions for the challenges of mental illness. Persons living with mental illness receive services and supports in multiple settings across the health care continuum that are often fragmented, uncoordinated, and inadequately responsive. Appropriate assessment is an important tool that health systems must deploy to respond to the strengths, preferences, and needs of persons with mental illness. However, standard approaches are often focused on measurement of psychiatric symptoms without taking a broader perspective to address issues like growth, development, and aging; physical health and disability; social relationships; economic resources; housing; substance use; involvement with criminal justice; stigma; and recovery. Using conglomerations of instruments to cover more domains is impractical, inconsistent, and incomplete while posing considerable assessment burden. interRAI mental health instruments were developed by a network of over 100 researchers, clinicians, and policy experts from over 35 nations. This includes assessment systems for adults in inpatient psychiatry, community mental health, emergency departments, mobile crisis teams, and long-term care settings, as well as a screening system for police officers. A similar set of instruments is available for child/youth mental health. The instruments form an integrated mental health information system because they share a common assessment language, conceptual basis, clinical emphasis, data collection approach, data elements, and care planning protocols. The key applications of these instruments include care planning, outcome measurement, quality improvement, and resource allocation. The composition of these instruments and psychometric properties are reviewed, and examples related to homeless are used to illustrate the various applications of these assessment systems.