What is prolong life, and how does it affect us?

Portfolio Project
Abstract
Health information technology supports the collection, aggregation and dissemination of
the health data. Electronic Health Records, a specific instance of this technology, enables the
sharing of health information between points of care. These tools are electronic compilations of a
patient’s health and medication history, provider visits, treatment pans and diagnostic
information, such as lab and radiology results. The use of health IT and health information
exchange can improve the quality of patient care, empower patients by supporting open
communication with providers, increase patient safety and save money for the system. In this
health care report, we study how the usage of electronic health record systems have impacted
quality of care, physician productivity, and hospital efficiency. Using research data, we show that
usage of electronic health record systems such as clinical decision support (CDS) is associated
with improved quality indicators. We show a positive correlation between the degree of
electronic health record (EHR) use and delegation of EHR tasks on clinician productivity.
Finally, we show that health information technology (HIT) adoption and hospital-physician
integration hospital positively impacts hospital efficiency.
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Portfolio Project
Introduction:
Data for this research study on electronic health records systems comes from the National
Hospital Medical Care Surveys, Athena health practice management system and EHR task logs,
American Hospital Association’s (AHA) annual survey, the AHA IT survey, CMS Case Mix
Index, and the US Census Bureau’s small area income and poverty estimates. The data covers
several periods from 1998 through 2014.
Prior research also supports the conclusion that the use of Electronic Health Records
systems positively impacts Health Care delivery. The research survey of databases consisting of
900 million outpatient primary care visits to clinics with EHRs from 2006-2009 show that the
presence of clinical decision support (CDS) was associated with improved blood pressure control
and increased number of visits not related to adverse drug events. The use of CDS was
associated with improvement in several quality indicators (Hsiao & Hing, 2012).
The data also shows that increased use of Electronic Health Records was associated with
increased productivity units for large hospitals and clinics where automation brought efficiency
to the operations. Greater EHR use and greater EHR task delegation were independently
associated with higher levels of productivity (Poissant et al, 2005).
EHR adoption and hospital-physician integration, individually, have statistically
significant positive impacts on hospital efficiency which shows that EHR adoption and hospital-
physician integration are key parts of improving hospital efficiency (Lammers, 2013).
Significance of the study:
The significance of this research study is that it shows that an EHR-based clinical
decision support system leads to modest but significant improvements in patient care. This
finding incentivizes physicians to learn EHR system use and transfer what they learned from
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Portfolio Project
using the clinical decision support system with some patients to the care of other patients. It also
enables health care administrators to recognize that EHR infrastructure will become ubiquitous
for personalization of medical care in the coming era of genomic medicine. EHR-embedded
clinical decision support may become an essential tool needed to systematically process complex
risk prediction data and then accurately identify appropriate clinical goals and high-priority
treatment options for each patient at each clinical encounter efficiency (Chaudhary, Wang & Wu,
2006). In summary, we aim to show that electronic health record systems (EHR) positively
impacts quality of care, physician productivity, and hospital.
Objectives are:
1. To determine whether usage of electronic health record systems such as clinical
decision support (CDS) is associated with improved quality indicators.
2. To examine the impact of the degree of electronic health record (EHR) use and
delegation of EHR tasks on clinician productivity.
3. To determine the impact of health information technology (HIT) adoption and
hospital-physician integration on hospital efficiency.