SELECT LABEL as CAREGIVER, drug, ICUSTAYS.icustay_id, CAST(ORIGINALAMOUNT AS INT) AS DOSE, first_careunit as Location
FROM CAREGIVERS
INNER JOIN INPUTEVENTS_CV
ON CAREGIVERS.CGID = INPUTEVENTS_CV.CGID
INNER JOIN ICUSTAYS
ON INPUTEVENTS_CV.ICUSTAY_ID = ICUSTAYS.ICUSTAY_ID
INNER JOIN PRESCRIPTIONS
ON ICUSTAYS.ICUSTAY_ID = PRESCRIPTIONS.ICUSTAY_ID
WHERE DRUG_NAME_GENERIC LIKE "FENTANYL citr%"
AND DOSE > 1000
AND CAREGIVER LIKE "RN"
Order by originalamountAnalysis Report Three - Information Systems and Healthcare Provider Interactions
Executive Summary
For decades in many hospitals and practitioners’ offices paper charts were the mainstay of healthcare “data.” The flimsy manila folders were alphabetized and held everything the doctor needed to know about the patient, until it didn’t. For example, if a patient went to another hospital or clinic without report from the patient no one would know other healthcare data for that patient existed. (Rinne et al. (2023)) Fast forward to today, healthcare data and the sheer amount of it is astounding. (DalleMule and Davenport (2017)) This is because of the invention of the Electronic Health Record or “EHR.” (Zandieh et al. (2008)) Now all patient information is filed in an electronic database that is dire to the function of the entire healthcare system. Thankfully, as these EHRs have evolved so have the ability to share data between the different EHRs and how patients and caregivers have learned to operate the patient side of the platforms to help easier contact their provider, view test results, and book appointments. (Weis et al. (2020))
Introduction
As time has passed and the invention of the internet and small, powerful computers so has the ability to create, share, and maintain data. With this boom of technology new inventions for healthcare are released everyday. One of the more recent changes to the information technology in healthcare is that of the Electronic Medical or Health Record. This are large, dynamic systems utilized by family practitioners, urgent cares, and hospital systems. Transition from paper to electronic documents did not catch right away. It has been a turbulent transition for some practitioners, patients, and healthcare systems. Practioners describe feeling a loss of relationship with the patient as they are having to focus on the computer rather than the patient. Others have developed work arounds to decrease their screen time and increase their patient time. As with anything new there are always challenges when it is first released but it is hard to walk around today and not hear patients talk about “MyChart”, for example.
Apps and systems like those that produce the data for “MyChart” are robust data management systems that integrate multiple departments within a facility, practitioners in a healthcare system, and patients who see practitioners are different facilities. (Rinne et al. (2023)) Coming a long way from paper charts, patients and caregivers are now very thankful for the use of electronic health records. For example, patients are able to add their caregivers or give them proxy to their electronic health record. (Weis et al. (2020)) The benefits of this capability is almost infinite as there is no more guessing what the doctor said the patient needed to do or when a patient’s next appointment is. (Adeniyi et al. (2024))
The Healthcare Context
Moving healthcare into the 21st century was quite the task for all healthcare systems. (Rinne et al. (2023)) Practitioners had done everything on paper from document visits, write prescriptions, and write orders in the hospital. Unfortunately, most practitioners in the age of paper had very difficult handwriting to decipher. This definitely helped some healthcare professionals be eager to adapt to the electronic medical record. (Rinne et al. (2023)) But this was not the case for most healthcare professionals.
Practitioners felt as though they were doing the patient a disservice by having to type and click around a screen rather than fully focusing on the patient. (Goni, Pertiwi, and Wariki (2025)) Granted as time has passed and training of clinicians has been completed with electronic medical records there is no turning back to ole pen and paper. (Murphy (2011)) Early adoption to EHR use was slow but many practitioners have come to see its value. Being able to easily click through a patient’s chart and see how their blood pressure has trended the past 6 months is quite helpful in making clinical decisions about the patient. This is just a simple example of the data available at a clinicians finger tips.
One of the biggest problems the implementation of EHRs faced was that most of them were built by information technologist - not healthcare practitioners. This led to a lot of confusion in the implementation process as the software was “clunky” and not user-friendly. As healthcare professionals do with anything that doesn’t work they either avoid it or work around it. (Laukka et al. (2020)) With such a push from management practitioners had no choice but to document their visits in the electronic health record. (Laukka et al. (2020)) This has a lot to do with the billing and coding users being able to properly bill a patient’s insurance for the services provided. However, the work arounds are normally looked at as a “negative approach” to operating the electronic health record. (Goni, Pertiwi, and Wariki (2025)) But in fact these work arounds help provide those who can alter the software insight into how clinicians think and what they could change to incorporate or even prevent the work around. (Zandieh et al. (2008))
At first caregivers and patients were not the happiest to transition to an EHR. (Weis et al. (2020)) When most of the systems originated most patients still had flip phones and TVs that weighed as much as a small child. So, the concept of having all their health data seemed to be impossible. However, when these systems got a grip, patients and caregivers were some of the more likable adapters. (Amiri et al. (2023)) A mother could now have all their child’s information in one place whether it was a vaccine, surgery at hospital A, and pediatrician visit at hospital B. The power of integration and the laws that govern release of a patient’s information to the patient immediately have greatly helped decrease the learning curb of navigating EHRs for patients. Not to mention patients are now able to better understand what their health looks like and what they need to do to get better.
Data Visualizations
Visualization One: Number of Fentanyl Citrate doses > 1000 mcg given by RNs to ICU Patients and Their Location
#Put your ggplot visualization in this block
ggplot(data = myquery1,
mapping = aes(x = Location)) +
geom_bar(fill = "orange") +
theme_minimal() +
labs(
title = "Number of Fentanyl Citrate doses > 1000 mcg \n given by RNs to ICU Patients and Their Location",
subtitle = "Data taken from CAREGIVERS, INPUTEVENTS_CV, ICUSTAYS, & PRESCRIPTIONS",
x = "Specific ICU Location",
y = "Number of Fentanyl Citrate Doses Given by RNs",
caption = "Source: MIMICIII Clinical Database v1.4"
)
This visualization provides the number of Fentanyl Citrate doses greater than 1000 mcg provided to patients in the CCU, MICU, and TSICU whose caregiver was a RN. Drug use is an important topic healthcare systems as this is one of the biggest expenses to hospitals. Thus, maintaining proper use, proper doses, and proper inventory are vital to the continuation of a hospital’s operations. There are also a derogatory side to this analysis as it provides analyzers with the amount of Fentanyl greater than 1000 mcg that SHOULD have been administered to the patient. Drug diversion is a big topic in healthcare and especially in hospitals. Granted with doses this high if a nurse or any healthcare professional tried to divert any fentanyl they would likely be found unconscious. However, many “safeties” are in place such as witnesses of controlled substance disposal and double checking of doses by a fellow nurse.
Visualization Two: Number Yeast, Staph and Strep related to the Diagnosis of Sepsis, Pulmonary Edema, or Chest Pain
SELECT GENDER, org_name AS PATHOGEN, DIAGNOSIS, COUNT(ORG_NAME) as ORGCOUNT, label as Caregiver
FROM PATIENTS
INNER JOIN MICROBIOLOGYEVENTS
ON PATIENTS.SUBJECT_ID = MICROBIOLOGYEVENTS.subject_id
INNER JOIN ADMISSIONS
ON ADMISSIONS.SUBJECT_ID = PATIENTS.subject_id
INNER JOIN INPUTEVENTS_CV
ON ADMISSIONS.HADM_ID = INPUTEVENTS_CV.HADM_ID
INNER JOIN CAREGIVERS
ON INPUTEVENTS_CV.CGID = CAREGIVERS.CGID
WHERE GENDER like "F"
AND (DIAGNOSIS LIKE "PULMONARY EDE%"
OR DIAGNOSIS LIKE "SEPSIS%"
OR DIAGNOSIS LIKE "CHEST PAIN%")
AND (PATHOGEN LIKE "YEAST"
OR PATHOGEN LIKE "STREP%"
OR PATHOGEN LIKE "STAPH%")
AND Caregiver = "RN"
GROUP BY DIAGNOSIS#Put your ggplot visualization in this block
ggplot(data = myquery2,
aes(x = diagnosis, y = ORGCOUNT, fill = PATHOGEN)) +
geom_col() +
theme_minimal() +
theme(axis.text.x = element_text(size = 4)) +
labs(
title = "Number Yeast, Staph and Strep related to the Diagnosis of \n Sepsis, Pulmonary Edema, or Chest Pain",
subtitle = "Data taken from PATIENTS, MICROBIOLOGYEVENTS, INPUTEVENTS_CV, \n CAREGIVERS, & ADMISSIONS",
x = "PATHOGEN COUNT",
y = "DIAGNOSIS",
caption = "Source: MIMIC-III Clinical Database v1.4"
)
This visualization demonstrates the specific diagnoses of patients in the ICU that were found out to be caused by Yeast, Streptococcus pneumoniae, or COAG NEG Staphylococcus. All of the patients had a caregiver of that was a RN. This information is important to hospitals especially when considering infection control and prevention. Entire departments are devoted to infection control. This data gives the analyzer the ability to determine what might have caused the cultures or tests to result with the given pathogen for each diagnosis. This helps clinicians better understand how to empirically treat patients until cultures and sensitivities result and provide more specific information about what pathogen the patient has and what medications will treat it.
Recommendations for Industry
Overall, healthcare has a large amount of data that is collected on each patient that is entered into their electronic health record. From multiple vital checks, drug administrations, and weights to operations and diagnostic tests. The sheer amount of data available at the fingertips of a practitioner utilizing an EHR is essentially limitless. Granted there are moments when some healthcare systems have not allowed the sharing of a patient’s health information between facilities but for the most part a practitioner has a well-informed image of the patient before they even walk into the room. (Rinne et al. (2023))
Operationally, there is no other way for a healthcare organization to function without an electronic health record. (Rinne et al. (2023)) There are too many metrics and patients for paper charts to be able to keep up. An average family practitioner sees around 40 patients a day - there is no humanly possible way to keep up with what the plan is for each patient and how the visit should be billed than utilizing the electronic health record. Granted the drawback of losing the personal connection with the patient has been quite the gripe of may practitioners but most electronic health records offer applications able to be installed on a tablet. (Laukka et al. (2020)) This is essentially 21st century paper as the practitioner can easily carry on a conversation with the patient while still entering information into the chart. Despite all efforts a health care system will try to get practitioners to use the electronic health record, there will always be practitioners who write everything down on paper and translate it into the EHR later.
On the defensive side of data, the electronic health record creates a nightmare for healthcare systems. The system now has this humongous amount of data to protect as required by HIPAA. Then with the introduction of patient access via apps on a telephone or computer this has is a nightmare for trying to keep the data protected. (Goni, Pertiwi, and Wariki (2025)) Despite the cost of protection, it is priceless for a patient to be able to instant access to everything to do with their healthcare. (Niazkhani et al. (2020)) With better informed patients, comes better patient outcomes and healthcare systems are always focused on patient outcomes. Thus, the money the system has to invest to maintain a defended database for their patients to access should be of no issue as this helps all patients live better and have higher quality of life.
References
Adeniyi, Adekunle Oyeyemi, Jeremiah Olawumi Arowoogun, Rawlings Chidi, Chioma Anthonia Okolo, and Oloruntoba Babawarun. 2024. “The Impact of Electronic Health Records on Patient Care and Outcomes: A Comprehensive Review.” World Journal of Advanced Research and Reviews 21 (2): 1446–55.
Amiri, Parastoo, Habibollah Pirnejad, Kambiz Bahaadinbeigy, Mahdie Shojaei Baghini, Parviz Rashidi Khazaee, and Zahra Niazkhani. 2023. “A Qualitative Study of Factors Influencing ePHR Adoption by Caregivers and Care Providers of Alzheimer’s Patients: An Extension of the Unified Theory of Acceptance and Use of Technology Model.” Health Science Reports 6 (7): e1394.
DalleMule, Leandro, and Thomas H Davenport. 2017. “What’s Your Data Strategy.” Harvard Business Review 95 (3): 112–21.
Goni, Angelina, Junita Maja Pertiwi, and Windy Wariki. 2025. “Analysis of Barriers to the Implementation of Electronic Medical Records in the Outpatient Clinic of Gunung Maria Hospital, Tomohon.” Pancasakti Journal Of Public Health Science And Research 5 (2): 231–37.
Laukka, Elina, Moona Huhtakangas, Tarja Heponiemi, and Outi Kanste. 2020. “Identifying the Roles of Healthcare Leaders in HIT Implementation: A Scoping Review of the Quantitative and Qualitative Evidence.” International Journal of Environmental Research and Public Health 17 (8): 2865.
Murphy, Judy. 2011. “Leading from the Future: Leadership Makes a Difference During Electronic Health Record Implementation.” Frontiers of Health Services Management 28 (1): 25–30.
Niazkhani, Zahra, Esmaeel Toni, Mojgan Cheshmekaboodi, Andrew Georgiou, and Habibollah Pirnejad. 2020. “Barriers to Patient, Provider, and Caregiver Adoption and Use of Electronic Personal Health Records in Chronic Care: A Systematic Review.” BMC Medical Informatics and Decision Making 20 (1): 153.
Rinne, Seppo T, Julian Brunner, David C Mohr, Adena-Cohen Bearak, and Ekaterina Anderson. 2023. “Practices Supporting Electronic Health Record Transitions: Lessons from Four US Healthcare Systems.” Journal of General Internal Medicine 38 (Suppl 4): 1015.
Weis, Aline, Sabrina Pohlmann, Regina Poss-Doering, Beate Strauss, Charlotte Ullrich, Helene Hofmann, Dominik Ose, Eva C Winkler, Joachim Szecsenyi, and Michel Wensing. 2020. “Caregivers’ Role in Using a Personal Electronic Health Record: A Qualitative Study of Cancer Patients and Caregivers in Germany.” BMC Medical Informatics and Decision Making 20 (1): 158.
Zandieh, Stephanie O, Kahyun Yoon-Flannery, Gilad J Kuperman, Daniel J Langsam, Daniel Hyman, and Rainu Kaushal. 2008. “Challenges to EHR Implementation in Electronic-Versus Paper-Based Office Practices.” Journal of General Internal Medicine 23 (6): 755–61.