Medical Record Accuracy begins with identifying the primary caregivers and the medical providers. It continues with the creation of a medical record. An individual or group of individuals work together to create and maintain a medical record for a patient. This information is used to aid healthcare providers, health insurance companies, and other medical professionals. Hospitals must ensure a patients medical document stays safe.
OBJECTives: The pilot project sought to test how well two groups of patients with similar demographics and backgrounds perform within a clinical trial when monitored by a Clinical Information Management System (CIMS). Identifying the primary care providers and the type of trial they oversee also identified key areas of improvement. The pilot tested four different types of CIMS supported Medication Intervention Sites (MIS) for four different trials involving diverse samples of patients with different backgrounds and medications. The pilot found that the two main types of CIMS supported Interactive Electronic Document Delivery System supported Interactive Electronic Document retrieval system performed significantly better than the trial record software that did not support the IMDs.
RESULTS: The pilot found that clinics and physicians correctly identified eligibility for all four trials; provided detailed clinically related data for all patients in all four trial fields; made adjustments for multiple site visits and out-patient time; and had no misclassification or incomplete data for any of the four variables. These factors are important to physicians when evaluating a trial participant. Out-patient time was specifically designated as one variable that allowed participants to be categorized based on the frequency of medication use. Medical record indexing can help to keep and retrieve patient information.
NEED FOR IMPLICIT FUNCTIONS: When the pilot tested four different types of CIMS supported Personal Health Record (PHR) enabled CEREC queries, it was discovered that many physicians and staff failed to correctly input these data. Based on this information, CIMS enabled Personal Health Record Improvement Programs were developed to help health care providers to input the required information with increased precision and ease.
A new improved PHR enabled Community Information Enterprise (CIE) could then query the Personal Health Record (PHR) and deliver results in terms of counts, percentages, standard deviations, and other expected data quality indications. The pilot conducted two different studies; in one study, there were no significant differences between groups for age, sex, race/ethnicity, area of practice, health status, length of time practicing, hospitalization and medication use, and referrals. In the second study, significant differences in rates were detected for the four categories (weighted scores, diabetes, cancer, asthma, and asthma/diseases) in both the presubscription group and the post Presubscription group.
RESULTS: The pilot tested four different subsample analyses using a maximum likelihood estimation approach. Using a maximum likelihood estimation approach, the first subsample analysis found that the accuracy of the total count, weighted, high variability components, and unweighted counts; the second subsample analysis found that the accuracy of weighted average odd ratios, high and low variance components, and percentage uniform random components was better than the first subsample analysis. Both of these subsample analyses showed strong evidence of pharmacist medication reconciliation errors.
The second study tested two different qualitative methods of correcting for errors in the PHR using quantitative analysis of the total counts, percentage of total changes, and percentages of total changes from one randomly selected patient to another. In this test, we found significant effects of PHR type on total counts, percentage changes, and variance components. PHR types were found to significantly affect the quality of care, and the number and percentage of patients who received undesired treatments and received adverse medical outcomes. The clinical governance group at the Center for Medicare & Medicaid Services, which managed the NPI process as part of their verification process for eligibility, concurred with the test results and recommendations.
Check this site and understand more about indexing records: https://en.wikipedia.org/wiki/Database_index.
