IU Indianapolis ScholarWorks :: Browsing by Author "Gibson, P. Joseph"

Browsing by Author "Gibson, P. Joseph"

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Characterizing Informatics Roles and Needs of Public Health Workers: Results from the Public Health Workforce Interests and Needs Survey
(Lippincott Williams & Wilkins, 2015-11) Dixon, Brian E.; McFarlane, Timothy D.; Dearth, Shandy; Grannis, Shaun J.; Gibson, P. Joseph; Department of Epidemiology, Richard M. Fairbanks School of Public Health
Objective: To characterize public health workers who specialize in informatics and to assess informatics-related aspects of the work performed by the public health workforce. Methods (Design, Setting, Participants): Using the nationally representative Public Health Workforce Interests and Needs Survey (PH WINS), we characterized and compared responses from informatics, information technology (IT), clinical and laboratory, and other public health science specialists working in state health agencies. Main Outcome Measures: Demographics, income, education, and agency size were analyzed using descriptive statistics. Weighted medians and interquartile ranges were calculated for responses pertaining to job satisfaction, workplace environment, training needs, and informatics-related competencies. Results: Of 10 246 state health workers, we identified 137 (1.3%) informatics specialists and 419 (4.1%) IT specialists. Overall, informatics specialists are younger, but share many common traits with other public health science roles, including positive attitudes toward their contributions to the mission of public health as well as job satisfaction. Informatics specialists differ demographically from IT specialists, and the 2 groups also differ with respect to salary as well as their distribution across agencies of varying size. All groups identified unmet public health and informatics competency needs, particularly limited training necessary to fully utilize technology for their work. Moreover, all groups indicated a need for greater future emphasis on leveraging electronic health information for public health functions. Conclusions: Findings from the PH WINS establish a framework and baseline measurements that can be leveraged to routinely monitor and evaluate the ineludible expansion and maturation of the public health informatics workforce and can also support assessment of the growth and evolution of informatics training needs for the broader field. Ultimately, such routine evaluations have the potential to guide local and national informatics workforce development policy.
Completeness and timeliness of notifiable disease reporting: a comparison of laboratory and provider reports submitted to a large county health department
(Springer Nature, 2017-06-23) Dixon, Brian E.; Zhang, Zuoyi; Lai, Patrick T. S.; Kirbiyik, Uzay; Williams, Jennifer; Hills, Rebecca; Revere, Debra; Gibson, P. Joseph; Grannis, Shaun J.; BioHealth Informatics, School of Informatics and Computing
BACKGROUND: Most public health agencies expect reporting of diseases to be initiated by hospital, laboratory or clinic staff even though so-called passive approaches are known to be burdensome for reporters and produce incomplete as well as delayed reports, which can hinder assessment of disease and delay recognition of outbreaks. In this study, we analyze patterns of reporting as well as data completeness and timeliness for traditional, passive reporting of notifiable disease by two distinct sources of information: hospital and clinic staff versus clinical laboratory staff. Reports were submitted via fax machine as well as electronic health information exchange interfaces. METHODS: Data were extracted from all submitted notifiable disease reports for seven representative diseases. Reporting rates are the proportion of known cases having a corresponding case report from a provider, a faxed laboratory report or an electronic laboratory report. Reporting rates were stratified by disease and compared using McNemar's test. For key data fields on the reports, completeness was calculated as the proportion of non-blank fields. Timeliness was measured as the difference between date of laboratory confirmed diagnosis and the date the report was received by the health department. Differences in completeness and timeliness by data source were evaluated using a generalized linear model with Pearson's goodness of fit statistic. RESULTS: We assessed 13,269 reports representing 9034 unique cases. Reporting rates varied by disease with overall rates of 19.1% for providers and 84.4% for laboratories (p < 0.001). All but three of 15 data fields in provider reports were more often complete than those fields within laboratory reports (p <0.001). Laboratory reports, whether faxed or electronically sent, were received, on average, 2.2 days after diagnosis versus a week for provider reports (p <0.001). CONCLUSIONS: Despite growth in the use of electronic methods to enhance notifiable disease reporting, there still exists much room for improvement.
Electronic Health Record (EHR)-Based Community Health Measures: An Exploratory Assessment of Perceived Usefulness by Local Health Departments
(BMC, 2018-05-22) Comer, Karen F.; Gibson, P. Joseph; Zou, Jian; Rosenman, Marc; Dixon, Brian E.; Health Policy and Management, School of Public Health
BACKGROUND: Given the widespread adoption of electronic health record (EHR) systems in health care organizations, public health agencies are interested in accessing EHR data to improve health assessment and surveillance. Yet there exist few examples in the U.S. of governmental health agencies using EHR data routinely to examine disease prevalence and other measures of community health. The objective of this study was to explore local health department (LHD) professionals' perceptions of the usefulness of EHR-based community health measures, and to examine these perceptions in the context of LHDs' current access and use of sub-county data, data aggregated at geographic levels smaller than county. METHODS: To explore perceived usefulness, we conducted an online survey of LHD professionals in Indiana. One hundred and thirty-three (133) individuals from thirty-one (31) LHDs participated. The survey asked about usefulness of specific community health measures as well as current access to and uses of sub-county population health data. Descriptive statistics were calculated to examine respondents' perceptions, access, and use. A one-way ANOVA (with pairwise comparisons) test was used to compare average scores by LHD size. RESULTS: Respondents overall indicated moderate agreement on which community health measures might be useful. Perceived usefulness of specific EHR-based community health measures varied by size of respondent's LHD [F(3, 88) = 3.56, p = 0.017]. Over 70% of survey respondents reported using community health data, but of those < 30% indicated they had access to sub-county level data. CONCLUSION: Respondents generally preferred familiar community health measures versus novel, EHR-based measures that are not in widespread use within health departments. Access to sub-county data is limited but strongly desired. Future research and development is needed as LHD staff gain access to EHR data and apply these data to support the core function of health assessment.
An Examination of How National Policies are Driving Population Health Outcomes and Organizational Change in Private and Public Sectors
(2020-03) Hilts, Katy Ellis; Menachemi, Nir; Blackburn, Justin; Gibson, P. Joseph; Halverson, Paul K.; Yeager, Valerie A.
The United States spends more on healthcare than any other country in the world, but still trails most other countries when it comes to important health indicators. There has been an increasing recognition that in order to address this discrepancy, the U.S. health system must begin to address the underlying social determinants contributing to poor health outcomes. In light of this, the concept of “population health” has emerged as a framework and model for how to better address the social determinants contributing to unhealthy behaviors and increased rates of morbidity and mortality in the U.S. Various national initiatives, including reform related to how doctors and hospitals are paid, have been developed with the purpose of increasing the adoption of strategies to address population health among public and private organizations. In this dissertation I attempt to assess how these national policies are driving behavior and outcomes related to improving population health in private and public sectors. It is comprised of three papers focused on 1) a systematic review of literature to assess how hospitals are responding to policies that encourage them to form partnerships to address population health, 2) a quantitative analysis of how the Affordable Care Act has impacted population health by addressing tobacco use with policies to increase Medicaid coverage for tobacco cessation services, and 3) an empirical examination to identify hospital strategic partnerships to address population health and determine hospital and market characteristics associated with these partnerships. The main findings of this study indicate that while there is a growing amount of peer reviewed literature focused on hospital partnerships for population health there is still a need for more generalizable studies with rigorous study designs in this area; Medicaid Expansion as a part of the Affordable Care Act is associated with lower prevalence of tobacco use; and policies, such as Accountable Care Organization and Bundled Payment models, may be influencing hospitals to engage with a broad set of partners to support population health activities. Collectively these studies provide new evidence to suggest that national policies may be driving behavior in private and public sectors related to population health.
Hospital Partnerships for Population Health: A Systematic Review of the Literature
(Wolters Kluwer, 2021) Ellis Hilts, Katy; Yeager, Valerie A.; Gibson, P. Joseph; Halverson, Paul K.; Blackburn, Justin; Menachemi, Nir; Health Policy and Management, School of Public Health
The U.S. healthcare system continues to experience high costs and suboptimal health outcomes that are largely influenced by social determinants of health. National policies such as the Affordable Care Act and value-based payment reforms incentivize healthcare systems to engage in strategies to improve population health. Healthcare systems are increasingly expanding or developing new partnerships with community-based organizations to support these efforts. We conducted a systematic review of peer-reviewed literature in the United States to identify examples of hospital-community partnerships; the main purposes or goals of partnerships; study designs used to assess partnerships; and potential outcomes (e.g., process- or health-related) associated with partnerships. Using robust keyword searches and a thorough reference review, we identified 37 articles published between January 2008 and December 2019 for inclusion. Most studies employed descriptive study designs (n = 21); health needs assessments were the most common partnership focus (n = 15); and community/social service (n = 21) and public health organizations (n = 15) were the most common partner types. Qualitative findings suggest hospital-community partnerships hold promise for breaking down silos, improving communication across sectors, and ensuring appropriate interventions for specific populations. Few studies in this review reported quantitative findings. In those that did, results were mixed, with the strongest support for improvements in measures of hospitalizations. This review provides an initial synthesis of hospital partnerships to address population health and presents valuable insights to hospital administrators, particularly those leading population health efforts.
Hospital Partnerships for Population Health: A Systematic Review of the Literature
(Wolters Kluwer, 2021) Ellis Hilts, Katy; Yeager, Valerie A.; Gibson, P. Joseph; Halverson, Paul K.; Blackburn, Justin; Menachemi, Nir; Global Health, School of Public Health
The U.S. healthcare system continues to experience high costs and suboptimal health outcomes that are largely influenced by social determinants of health. National policies such as the Affordable Care Act and value-based payment reforms incentivize healthcare systems to engage in strategies to improve population health. Healthcare systems are increasingly expanding or developing new partnerships with community-based organizations to support these efforts. We conducted a systematic review of peer-reviewed literature in the United States to identify examples of hospital-community partnerships; the main purposes or goals of partnerships; study designs used to assess partnerships; and potential outcomes (e.g., process- or health-related) associated with partnerships. Using robust keyword searches and a thorough reference review, we identified 37 articles published between January 2008 and December 2019 for inclusion. Most studies employed descriptive study designs (n = 21); health needs assessments were the most common partnership focus (n = 15); and community/social service (n = 21) and public health organizations (n = 15) were the most common partner types. Qualitative findings suggest hospital-community partnerships hold promise for breaking down silos, improving communication across sectors, and ensuring appropriate interventions for specific populations. Few studies in this review reported quantitative findings. In those that did, results were mixed, with the strongest support for improvements in measures of hospitalizations. This review provides an initial synthesis of hospital partnerships to address population health and presents valuable insights to hospital administrators, particularly those leading population health efforts.
Impact of Medicaid expansion on smoking prevalence and quit attempts among those newly eligible, 2011–2019
(EU European Publishing, 2021-08-05) Hilts, Katy Ellis; Blackburn, Justin; Gibson, P. Joseph; Yeager, Valerie A.; Halverson, Paul K.; Menachemi, Nir; Health Policy and Management, School of Public Health
Introduction: Low-income populations have higher rates of smoking and are disproportionately affected by smoking-related illnesses. This study assessed the long-term impact of increased coverage for tobacco cessation through Medicaid expansion on past-year quit attempts and prevalence of cigarette smoking. Methods: Using data from CDC's annual Behavioral Risk Factor Surveillance System 2011-2019, we conducted difference-in-difference regression analyses to compare changes in smoking prevalence and past-year quit attempts in expansion states versus non-expansion states. Our sample included non-pregnant adults (18-64 years old) without dependent children with incomes at or below 100% of the Federal Poverty Level (FPL). Results: Regression analyses indicate that Medicaid expansion was associated with reduced smoking prevalence in the first two years post-expansion (β=-0.019, p=0.04), but that this effect was not maintained at longer follow-up periods (β=-0.006, p=0.49). Results of regression analyses also suggest that Medicaid expansion does not significantly impact quit attempts in the short-term (β=-0.013, p=0.52) or at longer term follow-up (β=-0.026, p=0.08). Conclusions: Expanded coverage for tobacco cessation services through Medicaid alone may not be enough to increase quit-attempts or sustain a reduction in overall prevalence of smoking in newly eligible populations over time. Medicaid programs should consider additional strategies, such as public education campaigns and removal of barriers, to support cessation among enrollees.
An Improved Utility Driven Approach Towards K-Anonymity Using Data Constraint Rules
(2013-08-14) Morton, Stuart Michael; Mahoui, Malika; Palakal, Mathew J.; Gibson, P. Joseph; Kharrazi, Hadi
As medical data continues to transition to electronic formats, opportunities arise for researchers to use this microdata to discover patterns and increase knowledge that can improve patient care. Now more than ever, it is critical to protect the identities of the patients contained in these databases. Even after removing obvious “identifier” attributes, such as social security numbers or first and last names, that clearly identify a specific person, it is possible to join “quasi-identifier” attributes from two or more publicly available databases to identify individuals. K-anonymity is an approach that has been used to ensure that no one individual can be distinguished within a group of at least k individuals. However, the majority of the proposed approaches implementing k-anonymity have focused on improving the efficiency of algorithms implementing k-anonymity; less emphasis has been put towards ensuring the “utility” of anonymized data from a researchers’ perspective. We propose a new data utility measurement, called the research value (RV), which extends existing utility measurements by employing data constraints rules that are designed to improve the effectiveness of queries against the anonymized data. To anonymize a given raw dataset, two algorithms are proposed that use predefined generalizations provided by the data content expert and their corresponding research values to assess an attribute’s data utility as it is generalizing the data to ensure k-anonymity. In addition, an automated algorithm is presented that uses clustering and the RV to anonymize the dataset. All of the proposed algorithms scale efficiently when the number of attributes in a dataset is large.
Improving Notifiable Disease Case Reporting Through Electronic Information Exchange–Facilitated Decision Support: A Controlled Before-and-After Trial
(Sage, 2020) Dixon, Brian E.; Zhang, Zuoyi; Arno, Janet N.; Revere, Debra; Gibson, P. Joseph; Grannis, Shaun J.; Epidemiology, School of Public Health
Objective: Outbreak detection and disease control may be improved by simplified, semi-automated reporting of notifiable diseases to public health authorities. The objective of this study was to determine the effect of an electronic, prepopulated notifiable disease report form on case reporting rates by ambulatory care clinics to public health authorities. Methods: We conducted a 2-year (2012-2014) controlled before-and-after trial of a health information exchange (HIE) intervention in Indiana designed to prepopulate notifiable disease reporting forms to providers. We analyzed data collected from electronic prepopulated reports and "usual care" (paper, fax) reports submitted to a local health department for 7 conditions by using a difference-in-differences model. Primary outcomes were changes in reporting rates, completeness, and timeliness between intervention and control clinics. Results: Provider reporting rates for chlamydia and gonorrhea in intervention clinics increased significantly from 56.9% and 55.6%, respectively, during the baseline period (2012) to 66.4% and 58.3%, respectively, during the intervention period (2013-2014); they decreased from 28.8% and 27.5%, respectively, to 21.7% and 20.6%, respectively, in control clinics (P < .001). Completeness improved from baseline to intervention for 4 of 15 fields in reports from intervention clinics (P < .001), although mean completeness improved for 11 fields in both intervention and control clinics. Timeliness improved for both intervention and control clinics; however, reports from control clinics were timelier (mean, 7.9 days) than reports from intervention clinics (mean, 9.7 days). Conclusions: Electronic, prepopulated case reporting forms integrated into providers' workflow, enabled by an HIE network, can be effective in increasing notifiable disease reporting rates and completeness of information. However, it was difficult to assess the effect of using the forms for diseases with low prevalence (eg, salmonellosis, histoplasmosis).
Institutional factors associated with hospital partnerships for population health: A pooled cross-sectional analysis
(Wolters Kluwer, 2022) Ellis Hilts, Katy; Gibson, P. Joseph; Blackburn, Justin; Yeager, Valerie A.; Halverson, Paul K.; Menachemi, Nir; School of Nursing
Background: Hospitals are increasingly engaging in partnerships to address population health in response to national policies, such as value-based payment models. However, little is known about how institutional factors influence hospital partnerships for population health. Purpose: Guided by institutional theory, we examine the association between institutional pressures (coercive, normative, and mimetic isomorphism) and hospital partnerships for population health. Methodology: A pooled cross-sectional analysis used an unbalanced panel of 10,777 hospital-year observations representing respondents to a supplemental question of the American Hospital Association's annual survey (2015-2017). The analysis included descriptive and bivariate statistics, and regression models that adjusted for repeated observations to examine the relationship between key independent variables and partnerships over time. Findings: In regression analyses, we found the most support for measures of coercive (e.g., regulatory factors) isomorphism, with nonprofit status, participation in accountable care organizations, and acceptance of bundled payments, all being consistently and significantly associated with partnerships across all organization types. Modest increases were observed from 2015 to 2017 for hospital partnerships with public health organizations (+2.8% points, p < .001), governmental organizations (+2.0% points, p = .009), schools (+4.1% points, p < .001), and businesses (+2.2% points, p = .007). Practice implications: Our results suggest that institutional factors, particularly those related to regulatory policies and programs, may influence hospital partnerships to support population health. Findings from this study can assist hospital leaders in assessing the factors that can support or impede the creation of partnerships to support their population health efforts.

Browsing by Author "Gibson, P. Joseph"

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