Implementation of Electronic Records in a Medical Practice Setting

2015 ◽  
pp. 96-106
Author(s):  
Jami M. Clark

Seneca Medical Center is a primary care practice that implemented an electronic medical record system in 2005. Since implementation, the practice has added different practice locations and its own lab. The implementation was smooth because the practice leadership had a positive message about the change and reasons for it. Physical space for housing charts of a growing practice, the drive toward quality, safety, efficiency, and future growth were factors that led to the transition to an electronic medical record system. Choosing a quality vendor, understanding the concerns and components involved, and excitement about change create an environment for a successful implementation.

Author(s):  
Jami M. Clark

Seneca Medical Center is a primary care practice that implemented an electronic medical record system in 2005. Since implementation, the practice has added different practice locations and its own lab. The implementation was smooth because the practice leadership had a positive message about the change and reasons for it. Physical space for housing charts of a growing practice, the drive toward quality, safety, efficiency, and future growth were factors that led to the transition to an electronic medical record system. Choosing a quality vendor, understanding the concerns and components involved, and excitement about change create an environment for a successful implementation.


2016 ◽  
Vol 34 (3_suppl) ◽  
pp. 75-75
Author(s):  
Pamela Kim Washington ◽  
Yan Li ◽  
Dennis S Durzinsky ◽  
James Duffy ◽  
Veronica Shim ◽  
...  

75 Background: Beginning in 2015, the Commission on Cancer (CoC) requires accredited facilities to provide eligible patients with a Survivorship Care Plan (SCP). While the benefits of SCPs in the quality and continuity of care are well documented in the literature, there is a dearth of information regarding best practices for implementation. Here we describe lessons learned in the development of a SCP at the Kaiser Permanente Oakland Medical Center (OMC). Methods: Adult patients with a diagnosis of stage 1-3 cancer who received curative treatment were identified by the Northern California Kaiser Permanente Cancer Registrar. Consistent with CoC guidelines for 2015, 10% of all eligible patients (n = 1160) are required to receive a SCP 3-6 months following active treatment. Thus, a total of 116 patients with a diagnosis of breast, colon, lung/bronchus, prostate, or melanoma of the skin at OMC were given a SCP. The implementation timeframe was July to December 2015. Use of a modified ASCO template was recommended for its rigor across the required domains. Following template approval by the Comprehensive Cancer Committee (CCC), a workflow consisting of identifying patients’ last treatment and manual data entry by a Physician Assistant (PA) as well as automated data population in the Kaiser Permanente electronic medical record system was developed. Completed SCPs were then provided to patients during a clinic visit. The workflow process was refined as appropriate based on feedback from staff & physicians. Results: Depending on the scope of treatment, mean preparation time is 10 minutes per plan using specific diagnosis codes via an electronic medical record system. Further, it takes 30 minutes for a PA or other Ancillary personnel to discuss the plan with a patient. Patient response was generally positive upon receipt of the plan. Conclusions: Successful SCP implementation is contingent upon engagement from multiple stakeholders. Per standard CoC 3.3, the implementation rate will increase annually from 10% in 2015 to 100% by 2019. Careful consideration to workflow processes and resources planning be must factored into achieving 100% compliance across all disease sites by 2019.


Healthcare ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 749
Author(s):  
Gumpili Sai Prashanthi ◽  
Nareen Molugu ◽  
Priyanka Kammari ◽  
Ranganath Vadapalli ◽  
Anthony Vipin Das

India is home to 1.3 billion people. The geography and the magnitude of the population present unique challenges in the delivery of healthcare services. The implementation of electronic health records and tools for conducting predictive modeling enables opportunities to explore time series data like patient inflow to the hospital. This study aims to analyze expected outpatient visits to the tertiary eyecare network in India using datasets from a domestically developed electronic medical record system (eyeSmart™) implemented across a large multitier ophthalmology network in India. Demographic information of 3,384,157 patient visits was obtained from eyeSmart EMR from August 2010 to December 2017 across the L.V. Prasad Eye Institute network. Age, gender, date of visit and time status of the patients were selected for analysis. The datapoints for each parameter from the patient visits were modeled using the seasonal autoregressive integrated moving average (SARIMA) modeling. SARIMA (0,0,1)(0,1,7)7 provided the best fit for predicting total outpatient visits. This study describes the prediction method of forecasting outpatient visits to a large eyecare network in India. The results of our model hold the potential to be used to support the decisions of resource planning in the delivery of eyecare services to patients.


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