In December 2022, the National Health Commission announced the "** Hospital Grade Evaluation Standards (2022 Edition)" (hereinafter referred to as the "National Standards"), which has been updated and revised compared with the previous edition, and the proportion of daily monitoring indicators has reached more than 60%. The increase in monitoring data has undoubtedly increased the requirements for the informatization construction level of the participating hospitals, and hospitals need to continuously improve their data governance capabilities to meet the increasingly comprehensive and rigorous requirements of monitoring indicators.
01 There are more than 1,000 hospital grade evaluation indicators
The national "Standard" is an updated revision of the 2020 version of the evaluation standards and their detailed rules, without major adjustments to the main framework and content, but incorporating the latest policies and normative requirements issued in recent years, and revising and improving some general terms and codes according to the development of the industry.
Following the release of the national version of the evaluation standards, all provinces and cities across the country have also updated them in light of local conditions, and many provinces have further refined the requirements for medical service capabilities and quality and safety monitoring data. Among the evaluation criteria, the second part of the comprehensive score of "medical service capacity and quality and safety monitoring data" has the heaviest weight, accounting for 60%. The content includes daily monitoring data such as hospital resource allocation, quality, safety, service, performance and other indicators, DRG evaluation, single disease, key medical technology quality control, and evaluation indicators of specialized hospitals.
The assessment of monitoring indicators aims to guide hospitals to pay attention to the completion of daily quality management and performance indicators, and the provinces have also increased on the basis of the national version of the evaluation standards to improve the medical quality of hospitals in the province in a more targeted manner.
Whether it is the national or provincial evaluation standards for the first hospital grade, the number of monitoring indicators has reached hundreds, many of which are proportional, completion rate, median, etc., and a number of data need to be extracted from the hospital information system for statistics and analysis. After comprehensive calculation, the number of indicators that need to be extracted can reach thousands.
For example, the national "Standards" put forward a "in-hospital mortality rate of patients with low-risk ICD diseases" in the hospital quality index, and attached 115 ICD-10 for low-risk diseases (2019v2.).0) Encoding. This is calculated as the total number of hospitalized patients who died due to the coded low- and medium-risk disease and the total number of patients hospitalized due to the coded low- and medium-risk disease. The extraction of this monitoring indicator requires hospitals to capture the number of hospitalized patients related to 115 low-risk diseases, as well as the number of patients who died due to corresponding diseases, etc., and the actual data involved is 230.
The requirements of the index of "compliance rate of antimicrobial drug use records" in the quality control index of medical record management.
Among the key professional quality control indicators, the national "Standards" include 18 quality control indicators related to the standards, each standard has more than dozens of monitoring indicators, and more than 100 indicators need to be extracted. For example, in the "Quality Control Indicators for Medical Record Management", the 27 indicators monitored are all ratios such as completion rate, coincidence rate, and correctness rate, and the number that needs to be extracted exceeds 54. Taking the "compliance rate of antimicrobial use records" as an example, the main monitoring content is the proportion of the number of inpatient medical records corresponding to the doctor's order and disease course record of antimicrobial use to the total number of inpatients using antimicrobial drugs in the same period, and the associated data includes the completion and implementation of antimicrobial drugs in the doctor's orders and disease course records, as well as the number of relevant inpatients.
02 The difficulty of data extraction stems from the shortcomings of the information system
The extraction of thousands of indicators involves multiple information systems such as HIS, PACS, EMR, and outpatient systems, which puts forward high requirements for the data governance capabilities of hospitals. However, hospitals face many pain points when extracting, statistically and analyzing these data.
Due to the different degrees of informatization construction in various hospitals, there are deficiencies in the standardization and normalization of patient data. For example, the data that needs to be obtained for grade review involves multiple departments and different systems, but the information system of some hospitals does not cover all the business, or cannot extract all the data related to the indicators, resulting in some work needs to be carried out manually or by other means, which greatly affects the work efficiency and timeliness of the data.
Different information systems may be different from different manufacturers, and there are inconsistent data standards.
1. Inability to interconnect and share "information islands" and other "information islands". This may lead to quality problems in the extracted data, which cannot be used for comparison and analysis, affecting the accuracy of the extraction and statistics of quality indicators.
03 Solve data extraction challenges with intelligent tools
In order to solve these problems, hospitals need to start from the construction of informatization, and realize the efficient collection of medical service capabilities and quality and safety monitoring data by connecting information systems, strengthening data governance capabilities and strengthening management models.
First of all, hospitals need to connect information systems in tandem. Because the quality indicators of the hospital grade review involve many departments and systems, including almost all the core business systems of the hospital, it is necessary to build a set of intelligent systems for data collection, governance and analysis, extract data from various business systems, and standardize the extracted data to identify the text information related to the quality control indicators.
Second, hospitals need to develop unified data standards, such as using standard diagnostic coding systems, standard data formats, etc., to ensure data consistency and comparability. By building a data quality management system, the data collected, converted, and cleaned by the business system can be better applied to ensure the quality of the data.
Finally, hospitals need to strengthen the construction of management systems. Due to the large amount of data collected and the fact that most clinical departments are involved, it is necessary for the hospital management department to coordinate and form a team to interpret and discuss the indicators, form a consensus, and reach an expert consensus. At the same time, the hospital should also improve the management system, and consolidate the responsible departments and responsible persons for the indicators.
It is a relatively objective and efficient way to use data to reflect the medical quality, safety and service capabilities of hospitals. In the context of policies and review systems, many hospitals have chosen to introduce intelligent tools to improve data governance capabilities and medical management quality, and have achieved good application results.
For example, a hospital introduced a medical big data middle platform for business system data interaction, global governance of hospital data, and built a clinical data center, established a relatively complete operation analysis index system, and explored the construction of a smart medical quality control system. On the basis of the data formation of a data asset hierarchical model that can be shared and reused, the hospital quickly promotes data services to other application fields, effectively supports policy requirements such as data reporting, electronic medical record rating, interconnection evaluation, and hospital evaluation, improves the application level of information systems, and supports the construction goal of smart hospitals. At present, the hospital has passed the level 5 of electronic medical records and the fourth level of interconnection, and initially achieved the improvement of data quality and governance efficiency, as well as the independent management of data assets, laying a solid data foundation for the high-quality development of the hospital.