Dataset Information

Do Avoidable Hospitalization Rates among Older Adults Differ by Geographic Access to Primary Care Physicians?

ABSTRACT:

Objective

To investigate the association between older adults' potentially avoidable hospitalization rates and both a geographic measure of primary care physician (PCP) access and a standard bounded-area measure of PCP access.

Data sources

State physician licensure data from the Virginia Board of Medicine. Patient-level hospital discharge data from Virginia Health Information. Area-level data from the American Community Survey and the Area Health Resources Files. Virginia Information Technologies Agency road network data. US Census Bureau TIGER/Line boundary files.

Study design

We use enhanced two-step floating catchment area methods to calculate geographic PCP accessibility for each ZIP Code Tabulation Area in Virginia. We use spatial regression techniques to model potentially avoidable hospitalization rates.

Data collection/extraction

Geographic accessibility was calculated using ArcGIS. Physician locations were geocoded using TAMU GeoServices and ArcGIS.

Principal findings

Increased geographic access to PCPs is associated with lower rates of potentially avoidable hospitalization among older adults. This association is robust, allowing for spatial spillovers in spatial lag models.

Conclusions

Compared to bounded-area density measures, unbounded geographic accessibility measures provide more robust evidence that avoidable hospitalization rates are lower in areas with more PCPs per person. Results from our spatial lag models reveal the presence of positive spatial spillovers.

SUBMITTER: Daly MR

PROVIDER: S-EPMC6056577 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Do Avoidable Hospitalization Rates among Older Adults Differ by Geographic Access to Primary Care Physicians?

Daly Michael R MR Mellor Jennifer M JM Millones Marco M

Health services research 20170628

<h4>Objective</h4>To investigate the association between older adults' potentially avoidable hospitalization rates and both a geographic measure of primary care physician (PCP) access and a standard bounded-area measure of PCP access.<h4>Data sources</h4>State physician licensure data from the Virginia Board of Medicine. Patient-level hospital discharge data from Virginia Health Information. Area-level data from the American Community Survey and the Area Health Resources Files. Virginia Informat ...[more]

PMID: 28660679

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Project description:BackgroundIn 2020, primary care practices adopted telemedicine as an alternative to in-person visits. Little is known about whether access to telemedicine was equitable, especially among older patients. Our objectives were to (1) examine older adults' use of telemedicine versus in-person primary care visits and (2) compare hospitalization for ambulatory care sensitive conditions (ACSCs) between the groups.MethodsIn this retrospective cross-sectional study of 17,103 patients aged ≥65 years seen at 32 clinics in the Mid-Atlantic, primary care patients were classified into two groups-telemedicine versus in person-based on the first visit between March and May 2020 and followed up for 14 days. Using multivariable logistic regression, we measured the odds of being seen via telemedicine versus in person as a function of patient demographics, comorbidities, and week of study period. We then measured the odds of ACSC hospitalization by visit modality.ResultsMean age was 75.1 years (SD, 7.5), 60.6% of patients were female, 64.6% white, 28.1% black, and 2.0% Hispanic. Overall, 60.3% of patients accessed primary care via telemedicine. Black (vs. white) patients had higher odds of using telemedicine (adjusted odds ratio [aOR], 1.30; 95% CI, 1.14-1.47) and Hispanic (vs. not Hispanic) patients had lower odds (aOR, 0.63; 95% CI, 0.42-0.92). Compared with the in-person group, patients in the telemedicine group had lower odds of ACSC hospitalization (aOR, 0.78; 95% CI, 0.61-1.00). Among patients who used telemedicine, black patients had 1.43 higher odds of ACSC hospitalization (95% CI, 1.02-2.01) compared with white patients. Patients aged 85 or older seen via telemedicine had higher odds of an ACSC hospitalization (aOR, 1.60; 95% CI, 1.03-2.47) compared with patients aged 65-74.ConclusionsThese findings support the use of telemedicine for primary care access for older adults. However, the observed disparities highlight the need to improve care quality and equity regardless of visit modality.

Project description:IntroductionAvoidable hospitalizations are considered preventable given effective and timely primary care management and are an important indicator of health system performance. The ability to predict avoidable hospitalizations at the population level represents a significant advantage for health system decision-makers that could facilitate proactive intervention for ambulatory care-sensitive conditions (ACSCs). The aim of this study is to develop and validate the Avoidable Hospitalization Population Risk Tool (AvHPoRT) that will predict the 5-year risk of first avoidable hospitalization for seven ACSCs using self-reported, routinely collected population health survey data.Methods and analysisThe derivation cohort will consist of respondents to the first 3 cycles (2000/01, 2003/04, 2005/06) of the Canadian Community Health Survey (CCHS) who are 18-74 years of age at survey administration and a hold-out data set will be used for external validation. Outcome information on avoidable hospitalizations for 5 years following the CCHS interview will be assessed through data linkage to the Discharge Abstract Database (1999/2000-2017/2018) for an estimated sample size of 394,600. Candidate predictor variables will include demographic characteristics, socioeconomic status, self-perceived health measures, health behaviors, chronic conditions, and area-based measures. Sex-specific algorithms will be developed using Weibull accelerated failure time survival models. The model will be validated both using split set cross-validation and external temporal validation split using cycles 2000-2006 compared to 2007-2012. We will assess measures of overall predictive performance (Nagelkerke R2), calibration (calibration plots), and discrimination (Harrell's concordance statistic). Development of the model will be informed by the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) statement.Ethics and disseminationThis study was approved by the University of Toronto Research Ethics Board. The predictive algorithm and findings from this work will be disseminated at scientific meetings and in peer-reviewed publications.

Dataset Information

Do Avoidable Hospitalization Rates among Older Adults Differ by Geographic Access to Primary Care Physicians?

Objective

Data sources

Study design

Data collection/extraction

Principal findings

Conclusions

Publications

Do Avoidable Hospitalization Rates among Older Adults Differ by Geographic Access to Primary Care Physicians?

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