A new marker of primary care utilization - annual accumulated duration of time of visits

The Relationship Between Perceived Age Discrimination in the Healthcare System and Health: An Examination of a Multi-Path Model in a National Sample of Israelis Over the Age of 50

OBJECTIVES

The present study aims to examine possible pathways that potentially account for the relationship between perceived age discrimination in healthcare settings (as one form of ageism) and health outcomes.

METHODS

We relied on 1570 complete surveys, which constitute a representative national sample of adults aged 50 and above in Israel.

RESULTS

We found a direct link between perceived age discrimination and health outcomes. This link was partially mediated by self-perceptions of aging and subsequently by health behaviors (e.g., eating vegetables) and preventive health behaviors (e.g., medical check-ups). The link between perceived age discrimination and health behaviors was moderated by age, thus, particularly detrimental for older people over the age of 65 as compared with those between the ages of 50 and 65.

DISCUSSION

This study adds to the literature as it examines comprehensive mechanisms to account for the path between perceived age discrimination and health status. Our findings point to the unique aspects associated with perceived age discrimination, which potentially make older people more susceptible to its negative effects.

Factors Associated with Up-to-Date Colonoscopy Use Among Puerto Ricans in New York City, 2003-2016

BACKGROUND

Colorectal cancer is the second leading cause of cancer death among Hispanic Americans. Puerto Ricans are the second largest Hispanic subgroup in the USA and the largest in New York City, but little is known about predictors of colorectal cancer screening uptake in this population.

AIMS

We used the New York City Community Health Survey, a population-based telephone survey, to investigate predictors of up-to-date colonoscopy use over time among Puerto Ricans aged ≥ 50 years in NYC.

METHODS

We assessed the association between sociodemographic and medical factors and up-to-date colonoscopy use (defined as colonoscopy within the last 10 years) using univariable and multivariable logistic regression over six time periods: 2003-2005, 2006-2008, 2009-2010, 2011-2012, 2013-2014, and 2015-2016.

RESULTS

On multivariable analysis, age ≥ 65 years (OR 1.64-1.93 over three periods) and influenza vaccination (OR 1.86-2.17 over five periods) were the two factors most consistently associated with up-to-date colonoscopy use. Individuals without a primary care provider (OR 0.38-0.50 over three periods) and who did not exercise (OR 0.49-0.52 over two periods) were significantly less likely to have an up-to-date colonoscopy.

CONCLUSIONS

Older age, influenza vaccination, having a primary care provider, and exercise are independent predictors of up-to-date colonoscopy use among Puerto Ricans in NYC. Interventions to improve screening colonoscopy uptake among Puerto Ricans should be targeted to those aged 50-64 years and who do not have a primary care provider.

Consultation length in ambulatory clinic of Belgrade Emergency Medical Service

The aim of the study was to analyze and compare consultation lengths in Emergency Medical Service (EMS) Belgrade ambulatory clinic which relates to patient age, gender, existing diagnoses and prescribed treatment (therapy or referral to another healthcare institution). We analyzed the data from the electronic database on consultation lengths from one EMS Belgrade Ambulatory Clinic. For patients who were further referred to another healthcare institution transfer, the waiting time was included in the total consultation time. We used the statistical package SPSS 11.0 for Windows for the statistical processing. Statistical significance was defined for the level of p < 0.05. The average consultation time was 21.07 ± 13.44 minutes. Usually, it lasted between 10 to 20 minutes. Consultations lasted longer in female patients (21.68 minutes), patients over 65 years of age (24.65 minutes), in patients with multiple diagnoses (26.1 and 27.28 minutes), as well as in patients where therapy was prescribed and administered in the ambulatory clinic (25.72 minutes), or in patients referred to other healthcare institutions. Statistically, the differences were highly significant (p < 0.01). When considering patients' diagnoses, longest consultations were in patients diagnosed with infectious diseases (average 30.88 minutes), followed by patients diagnosed with diseases of the circulatory system (27.86 minutes) and patients with diseases of the respiratory system (21.56 minutes). The differences were statistically significant (p < 0.01). Patients' age, gender, disease diagnosis and administered therapy affect the consultations time. Depending on the diagnosis, consultations last longer for infectious, cardiovascular and respiratory diseases.

Providers and patients face-to-face: what is the time?

Background

The frequency of visiting primary care providers and the duration of those visits varies substantially by patient demographics and across different developed countries. The significance of a cumulative measure of this time spent with providers in face-to-face visits is not well understood.

Commentary

In a recent IJHPR issue Nathan and co-authors have suggested a new metric for capturing the cumulative time spent annually in face-to-face encounters between providers and patients. The annual accumulated duration of time (AADC) of visits was constructed using a 2% random sample of adult patients from the Clalit health plan in Israel for the year 2012. The authors calculated the mean AADC to be 65.7 min with average visit durations of 7.6 min. A presumption underlying this analysis is that the metric captures the magnitude of activity devoted to eliciting relevant clinical information, synthesizing the significance of those data, and communicating the importance of that thinking to patients so that they might make informed decisions regarding their health care. But measuring the time spent with a provider is but a surrogate marker of these activities and the lack of correlation between time spent with providers and health outcomes suggests that as a surrogate it may not be that robust a measure. It is possible that what is being captured through this metric is the influence of economic incentives faced by individual practitioners and the structure of health care financing in different societies rather than a portrait either of clinical complexity or quality of care.

Conclusions

The advent of this new measure of cumulative provider time with patients signals the importance of accurate measurement as a vital first step in understanding the meaning of data but reminds us of an obligation to inquire beyond the measurements themselves to arrive at appropriate policy-relevant conclusions.