Population Health Management Dashboard

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EXECUTIVE SUMMARY 7

Assessing Data Sets for Population Health Management Tallahassee, Florida

Whitney Gibson

January 20, 2022

Rasmussen University

HSA5300CBE Population Health

Assessing Data Sets for Tallahassee Population Health Management

To effectively manage a healthcare organization, the management has to be furnished with the latest data and information that has been compiled with great accuracy. From this compiled data, a healthcare manager is able to analyze the needs of patients and the strain on the hospital amenities. Without this data, it is impossible for a healthcare manager to gauge the effectiveness of health programs being implemented and the initiatives that the health center is undertaking in provision of quality healthcare. To arrive at this the required data, the healthcare provider can source it from the IT system used by the health center or from business partners. The data has to be accurate to give a more realistic depiction of the state of affairs in the health center. Developing a comprehensive data analysis approach helps a health manager effectively address the needs of the patients (Muller, Heimo et al. 2020). Without concrete data to fall back on it become impossible for healthcare providers to predict future health crisis due to a failure to analyze patterns.

When assessing data sets for the purpose of population health management, a huge emphasis has to be placed on the credibility of the collected data. Bad data will result into erroneous judgements that might put the health of patients at risk (Raghupathi et al. 2014). Due to the sensitive nature of the data being collected, the process has to be confidential to avoid exposing the information of patients to unauthorized parties. The data used for healthcare management has to be timely to capture all the emerging trends in health issues that are affecting patients. Outdated data cannot be relied on as it does not depict the current state of affairs, this makes it useless to a health manager as it only shows past patterns.

THE DIFFERENT DATA SETS FOR HEALTHCARE MANAGEMENT

Patient Demographics

Data collected on the demographics of the patients that visited a health center help the manager in assessing what diseases affect people in a certain age bracket or from a certain sex. Dividing up patients based on demographics gives healthcare providers insight on complications that are experienced by patients at different ages. The information is useful to a health center as it helps in strategic planning of health programs that target specific age groups or sexes. The information of patient demographics is useful in drawing observations on chronic diseases and lifestyle diseases helping a health center plan better on how to handle future patients and possible health programs that could be started to boost their recovery journey.

Vital Signs

When patients are admitted in a health center, it is common practice to check and record their vital signs. The data collected from the checkup is useful in drawing a diagnosis later as it gives insight on potential red flags. Vitals such as the heart rate, body temperature and respiratory rate are useful indicators on the state of health of an individual (Kenzaka et al. 2012). They are tell-tale signs of most chronic diseases and can be used to spot these diseases early to allow for more diligent care and treatment of the patients. Recording these vital signs helps a doctor draw a more accurate diagnostic as the signs serve as indicators on what might be troubling their patients and speed up the treatment process.

Laboratory Results

Clinical lab results are a crucial part of the treatment process as they offer a factual analysis of fluid and tissue from the patient. Lab results eliminate speculations from the treatment process and allow a health care provider to draw a more accurate diagnosis of a patient. Without these clinical reports, doctors would have to rely on wild speculations drawn from general observation to diagnose patients. Data collected from laboratory results is useful in identifying hereditary diseases early, this helps in seeking out early treatment once detected (Frazer et al. 2011). The data collected and compiled from laboratory results is important to health practitioners as it helps in drawing accurate diagnosis as it helps narrow down to the exact cause of a complication without leaving much to speculation.

Progress Notes

Doctors deal with a large number of patients daily, relying on memory would be a poor strategy. Data compiled from the progress notes made on each patient in their personal file helps track the progress of the patient more effectively. These progress notes give the doctor a more concrete reference point that helps in keeping track of how the patient is fairing. From the progress notes a medical practitioner can observe improvements in health made or deteriorations and remedy them before they grow into something severe. Progress notes give a tangible depiction of the state of health of a patient from the time they started treatment to the current stage, this helps in gauging the effectiveness of the treatment.

Problem Lists and Diagnoses

The data compiled from the problem list of a patient and past diagnoses helps to speed up the treatment process of a patient as it gives the doctor a detailed history of past complications the patient suffered. Without an elaborate patient history, a doctor might rush into diagnosing the wrong symptom without factoring in that it is a development from a past complication. The medical history of patients is crucial in drawing future treatment plans of these patients, data from the problem list and diagnoses is used to speed up the diagnoses process (Pine et al. 2012). With a well/ compiled list of patient problem list and past diagnoses, it becomes easier for health care providers to give referrals to their patients as the other medical centers will have something to work with.

Allergy Lists

A diligent medical provider has to have an extensive list of medical allergies that affect the patients seeking treatment at a health center. An allergy list helps the health care provider avoid making fatal errors that might result into severe reactions. The doctor has to inquire from the patient of any past allergies and record the findings. The compiled data helps in avoiding errors in prescribing medication by considering the allergies that the patient suffers from. Without this data, the doctor risks causing harm to the patient by offering treatment without due consideration of the potential risks.

Medication Data

As a health care provider, a comprehensive list of the medication that a patient has been on is extremely useful as it ensures that there are no instances of double medication for the same illness. The medication data list helps the doctor adjust the treatment plan of a patient to speed up the recovery process.

REFERENCES

Frazer-Abel, A., & Giclas, P. C. (2011, September). Update on laboratory tests for the diagnosis and differentiation of hereditary angioedema and acquired angioedema. In Allergy and Asthma Proceedings (Vol. 32, No. 5, p. 17). OceanSide Publications.

Kenzaka, T., Okayama, M., Kuroki, S., Fukui, M., Yahata, S., Hayashi, H., ... & Hashimoto, M. (2012). Importance of vital signs to the early diagnosis and severity of sepsis: association between vital signs and sequential organ failure assessment score in patients with sepsis. Internal Medicine, 51(8), 871-876.

Müller, H., Dagher, G., Loibner, M., Stumptner, C., Kungl, P., & Zatloukal, K. (2020). Biobanks for life sciences and personalized medicine: importance of standardization, biosafety, biosecurity, and data management. Current opinion in biotechnology, 65, 45-51.

Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health information science and systems, 2(1), 1-10.

Pine, M., Sonneborn, M., Schindler, J., Stanek, M., & Maeda, J. L. (2012). Harnessing the power of enhanced data for healthcare quality improvement: lessons from a Minnesota Hospital Association Pilot Project. Journal of Healthcare Management, 57(6), 406-418.