Prediction of Unmet Primary Care Needs for the Medically Vulnerable Post-Disaster: An Interrupted Time-Series Analysis of Health System Responses

Disasters serve as shocks and precipitate unanticipated disturbances to the health care system. Public health surveillance is generally focused on monitoring latent health and environmental exposure effects, rather than health system performance in response to these local shocks. The following inter...

Full description

Bibliographic Details
Main Authors: Amy B. Martin, Erik R. Svendsen, Jennifer D. Runkle, Hongmei Zhang, Wilfried Karmaus
Format: Article
Language:English
Published: MDPI AG 2012-09-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:http://www.mdpi.com/1660-4601/9/10/3384
id doaj-b25b4d818da944ef951ee2f32cd4d963
record_format Article
spelling doaj-b25b4d818da944ef951ee2f32cd4d9632020-11-24T23:08:41ZengMDPI AGInternational Journal of Environmental Research and Public Health1660-46012012-09-019103384339710.3390/ijerph9103384Prediction of Unmet Primary Care Needs for the Medically Vulnerable Post-Disaster: An Interrupted Time-Series Analysis of Health System ResponsesAmy B. MartinErik R. SvendsenJennifer D. RunkleHongmei ZhangWilfried KarmausDisasters serve as shocks and precipitate unanticipated disturbances to the health care system. Public health surveillance is generally focused on monitoring latent health and environmental exposure effects, rather than health system performance in response to these local shocks. The following intervention study sought to determine the long-term effects of the 2005 chlorine spill in Graniteville, South Carolina on primary care access for vulnerable populations. We used an interrupted time-series approach to model monthly visits for Ambulatory Care Sensitive Conditions, an indicator of unmet primary care need, to quantify the impact of the disaster on unmet primary care need in Medicaid beneficiaries. The results showed Medicaid beneficiaries in the directly impacted service area experienced improved access to primary care in the 24 months post-disaster. We provide evidence that a health system serving the medically underserved can prove resilient and display improved adaptive capacity under adverse circumstances (i.e., technological disasters) to ensure access to primary care for vulnerable sub-groups. The results suggests a new application for ambulatory care sensitive conditions as a population-based metric to advance anecdotal evidence of secondary surge and evaluate pre- and post-health system surge capacity following a disaster.http://www.mdpi.com/1660-4601/9/10/3384technological disastervulnerable populationsaccess to careambulatory care sensitive conditionssecondary surge capacityrecoveryhealth systemforecast modeling
collection DOAJ
language English
format Article
sources DOAJ
author Amy B. Martin
Erik R. Svendsen
Jennifer D. Runkle
Hongmei Zhang
Wilfried Karmaus
spellingShingle Amy B. Martin
Erik R. Svendsen
Jennifer D. Runkle
Hongmei Zhang
Wilfried Karmaus
Prediction of Unmet Primary Care Needs for the Medically Vulnerable Post-Disaster: An Interrupted Time-Series Analysis of Health System Responses
International Journal of Environmental Research and Public Health
technological disaster
vulnerable populations
access to care
ambulatory care sensitive conditions
secondary surge capacity
recovery
health system
forecast modeling
author_facet Amy B. Martin
Erik R. Svendsen
Jennifer D. Runkle
Hongmei Zhang
Wilfried Karmaus
author_sort Amy B. Martin
title Prediction of Unmet Primary Care Needs for the Medically Vulnerable Post-Disaster: An Interrupted Time-Series Analysis of Health System Responses
title_short Prediction of Unmet Primary Care Needs for the Medically Vulnerable Post-Disaster: An Interrupted Time-Series Analysis of Health System Responses
title_full Prediction of Unmet Primary Care Needs for the Medically Vulnerable Post-Disaster: An Interrupted Time-Series Analysis of Health System Responses
title_fullStr Prediction of Unmet Primary Care Needs for the Medically Vulnerable Post-Disaster: An Interrupted Time-Series Analysis of Health System Responses
title_full_unstemmed Prediction of Unmet Primary Care Needs for the Medically Vulnerable Post-Disaster: An Interrupted Time-Series Analysis of Health System Responses
title_sort prediction of unmet primary care needs for the medically vulnerable post-disaster: an interrupted time-series analysis of health system responses
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1660-4601
publishDate 2012-09-01
description Disasters serve as shocks and precipitate unanticipated disturbances to the health care system. Public health surveillance is generally focused on monitoring latent health and environmental exposure effects, rather than health system performance in response to these local shocks. The following intervention study sought to determine the long-term effects of the 2005 chlorine spill in Graniteville, South Carolina on primary care access for vulnerable populations. We used an interrupted time-series approach to model monthly visits for Ambulatory Care Sensitive Conditions, an indicator of unmet primary care need, to quantify the impact of the disaster on unmet primary care need in Medicaid beneficiaries. The results showed Medicaid beneficiaries in the directly impacted service area experienced improved access to primary care in the 24 months post-disaster. We provide evidence that a health system serving the medically underserved can prove resilient and display improved adaptive capacity under adverse circumstances (i.e., technological disasters) to ensure access to primary care for vulnerable sub-groups. The results suggests a new application for ambulatory care sensitive conditions as a population-based metric to advance anecdotal evidence of secondary surge and evaluate pre- and post-health system surge capacity following a disaster.
topic technological disaster
vulnerable populations
access to care
ambulatory care sensitive conditions
secondary surge capacity
recovery
health system
forecast modeling
url http://www.mdpi.com/1660-4601/9/10/3384
work_keys_str_mv AT amybmartin predictionofunmetprimarycareneedsforthemedicallyvulnerablepostdisasteraninterruptedtimeseriesanalysisofhealthsystemresponses
AT erikrsvendsen predictionofunmetprimarycareneedsforthemedicallyvulnerablepostdisasteraninterruptedtimeseriesanalysisofhealthsystemresponses
AT jenniferdrunkle predictionofunmetprimarycareneedsforthemedicallyvulnerablepostdisasteraninterruptedtimeseriesanalysisofhealthsystemresponses
AT hongmeizhang predictionofunmetprimarycareneedsforthemedicallyvulnerablepostdisasteraninterruptedtimeseriesanalysisofhealthsystemresponses
AT wilfriedkarmaus predictionofunmetprimarycareneedsforthemedicallyvulnerablepostdisasteraninterruptedtimeseriesanalysisofhealthsystemresponses
_version_ 1725612923734196224