How Collaboration Can Improve the Quality of Patient Care
2018
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The patient data available must be cleansed with the support of data cleansing services so that actionable, accurate data is obtained. To leverage the available data, active collaboration across the healthcare spectrum is crucial.
To achieve better healthcare outcome and greater life expectancy, the quality of healthcare services must be constantly evaluated and improved. This involves collecting and storing large quantities of patient data ranging from admission, diagnostic, treatment and discharge details to online interaction between patients and providers as well as information about the providers. The data available must be cleansed with the support of data cleansing services so that actionable, accurate data is obtained. To leverage the available data, active collaboration across the healthcare spectrum is necessary apart from a central data and analytics team, a standalone virtual data warehouse, and stringent data governance. With efficient connected systems, healthcare professionals and patients find themselves in a better place. It makes the operational process in the healthcare sector easy and more efficient with advanced technologies such as apps, telemedicine and so on, patients can communicate well with providers and providers can give customized services to patients. These online and mobile platforms not only empower patients but also enable healthcare organizations to better understand patients and their wants. At Sanford Health, care is provided to over 2.5 million people in 300 communities across 250,000 square miles under a $ 4.5 billion rural integrated healthcare system. In this process, all patient data is collected and stored. To improve patient care, Sanford collaborated with potential academic partners who were leading in data science, from various university departments. The collaboration was on projects that could improve healthcare quality and lower costs. Sanford created contracts that gave these partners access to data whose use had previously been restricted by concerns about data privacy and competitive use agreements. The Sanford Data Collaborations is in its second year and it has attracted regional and national partners. It has begun to deliver data driven that helps to improve care delivery, patient engagement and care access. In patients with chronic conditions, negligent management and poor follow-ups care increase the risk of emergency care visits or unplanned inpatient admission. Identifying patients who are risk and finding the clinical and behavioural characteristics associated with them can help frontline clinicians to provide target management. An algorithm developed by the University Of North Dakota School Of Medicine’s Population Health Department helps to predict diabetic patients’ risk of an unplanned medical visit. The algorithm analyzes smoking status,
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BMI and other diagnoses on a patient’s problem list. The algorithm is currently being validated in pilot clinics with the goal of scaling it up for enterprise. Patient engagement is an important element in healthcare and a significant predictor of healthcare behaviours and outcomes. Measuring patient engagement is often difficult because it is time-consuming, generally has low participation rates and only patients who are more engaged will be willing to take a survey. To tackle this issue, Sanford partnered with investigators from the Data Science and Health Science schools at South Dakota State University. They developed a patient engagement score algorithm for people with multiple chronic conditions using pre-existing patient behaviour data. The results predicted the likelihood of patient emergency department visits and hospitalization more accurately than other methods previously used. Provider turnover is a significant issue, especially for rural communities. It affects continuity of care and quality. To resolve this problem Sanford has partnered with healthcare economists at the Wharton School of Business to explore the drivers across settings and services areas that affect retention throughout the healthcare system. The goal is to identify predictors of turnover and retention and to develop policy recommendations to address this churn. The Stanford data collaboration is a new project which is in its initial stage but has the potential to improve the delivery of value in healthcare. It promises to improve patient outcomes by targeting care, reducing the need for unexpected care and applying behavioural economics to patient engagement and provider retention. In any data related project, healthcare systems and providers can utilize efficient data cleansing services and medical data entry services to obtain timely and actionable data. Service providers offer dedicated solutions that are affordable and professional.
www.managedoutsource.com
1-800-670-2809