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1.
Front Digit Health ; 4: 928602, 2022.
Article in English | MEDLINE | ID: mdl-36440462

ABSTRACT

Background: Digital health interventions are increasingly used for patient care, yet little data is available on the phone access type and usage preferences amongst medical ward inpatients to inform the most appropriate digital interventions post-discharge. Methods: To identify mobile phone ownership, internet access, and cellular use preferences among medical inpatients, we conducted a researcher-administered survey of patients admitted to five internal medicine units at Vancouver General Hospital (VGH) in January 2020. The survey was administered over 2 days separated by a 2-week period. Results: A total of 81 inpatients completed the questionnaire. Survey found that 85.2% of survey respondents had mobile phone access where 63.0% owned their own mobile phone, and 22.2% had access to a mobile phone via a proxy (or an authorized third-party) such as a family member. All participants with mobile phone access had cellular plans (i.e., phone and text); however, a quarter of respondents did not have data plans with internet access. Survey showed that 71.1% of males owned a mobile phone compared to only 52.8% of females. All participants at a "high" risk of readmission had access to a mobile phone, either as phone-owners or proxy-dependent users. Conclusion: Access to mobile phones among medical ward inpatients, 85.2%, was comparable to smartphone penetration rates amongst Canadians in 2019, 85.1%. More patients had cellular than data plans (i.e., internet and applications). Understanding patient-specific access is key to informing potential uptake of digital health interventions aimed at using patients' mobile phones (mHealth) from an effectiveness and equity lens.

2.
BMC Fam Pract ; 21(1): 98, 2020 05 31.
Article in English | MEDLINE | ID: mdl-32475339

ABSTRACT

BACKGROUND: Primary care serves all age groups and individuals with health states ranging from those with no chronic conditions to those who are medically complex, or frail and approaching the end of life. For information to be actionable and guide planning, there must be some population disaggregation based on differences in expected needs for care. Promising approaches to segmentation in primary care reflect both the breadth and severity of health states, the types and amounts of health care utilization that are expected, and the roles of the primary care provider. The purpose of this study was to assess population segmentation as a tool to create distinct patient groups for use in primary care performance reporting. METHODS: This cross-sectional study used administrative data (patient characteristics, physician and hospital billings, prescription medicines data, emergency department visits) to classify the population of British Columbia (BC), Canada into one of four population segments: low need, multiple morbidities, medically complex, and frail. Each segment was further classified using socioeconomic status (SES) as a proxy for patient vulnerability. Regression analyses were used to examine predictors of health care use, costs and selected measures of primary care attributes (access, continuity, coordination) by segment. RESULTS: Average annual health care costs increased from the low need ($ 1460) to frail segment ($10,798). Differences in primary care cost by segment only emerged when attributes of primary care were included in regression models: accessing primary care outside business hours and discontinuous primary care (≥5 different GP's in a given year) were associated with higher health care costs across all segments and higher continuity of care was associated with lower costs in the frail segment (cost ratio = 0.61). Additionally, low SES was associated with higher costs across all segments, but the difference was largest in the medically complex group (cost ratio = 1.11). CONCLUSIONS: Population segments based on expected need for care can support primary care measurement and reporting by identifying nuances which may be lost when all patients are grouped together. Our findings demonstrate that variables such as SES and use of regression analyses can further enhance the usefulness of segments for performance measurement and reporting.


Subject(s)
Community Health Planning/methods , Health Care Costs/statistics & numerical data , Patient Care Management , Primary Health Care , Quality of Health Care , British Columbia/epidemiology , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Needs Assessment/organization & administration , Patient Acceptance of Health Care/statistics & numerical data , Patient Care Management/methods , Patient Care Management/organization & administration , Patient Care Management/statistics & numerical data , Primary Health Care/organization & administration , Primary Health Care/standards , Process Assessment, Health Care/methods , Quality of Health Care/organization & administration , Quality of Health Care/standards , Risk Management
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