A Health Information Management (HIM) / Medical Records (MR) practitioner at any HIM / MR department in any hospital knows pretty well how often his or her hospital has determined how often different sets of clinical and administrative data that are collected during or in the time closely surrounding the patient encounter, are aggregated and analysed at his or her department or in other relevant departments. Patient records, uniform billing information, and discharge data sets are the main sources of the data that go into the literally hundreds of aggregate reports or queries that are developed and used by care providers and executives in hospitals. The frequency depends on the activity or area being measured, the frequency of measurement, and the hospital’s priorities.
What can these data then tell you about the hospital and the care provided to its patients?
How can you process these data into meaningful information?
The number of aggregate reports that could be developed from patient records or other patient related information – example accounting information, is practically as you already know is limitless.
Data quality management programs are essential for clinical improvement. Thus, HIM / MR practitioners must realise there is a need for the continuous quality improvement to ensure the accuracy and completeness of data collection at their end. HIM / MR practitioners frequently generate reports that yield data from their data collection. Such reports can then be used to help monitor patient outcomes and identify areas in which improved care is needed. However, HIM / MR practitioners need to regularly run and act upon them to improve areas of missing or incomplete data. They must also ensure that standard operating procedures in data management processes are in place, remedy inconsistent data collection methods, or minimise missing paper records. So I guess that more training and onsite audits could help facilitate additional improvement in data quality and efficiency.
In the post Data must be aggregated, analysed, and transformed into useful information by expert individuals (this link will open in a new tab of your current browser window), I had outlined the importance of data analysis that must involve individuals who understand information management, have skills in data aggregation methods, and know how to use various statistical tools.
HIM / MR practitioners must ensure that data collection up-to-date (data currency) and must be able to relate the frequency of data analysis (timeliness) appropriate to a process under study and develop processes that match frequency of data analysis to meet the hospital’s requirements.
The categories of statistics that are routinely gathered by HIM / MR practitioners in a hospital for data analysis include:
- Census statistics including the average daily census and bed occupancy rates from data collected in wards to reveal the number of patients present at any one time in a hospital.
- Discharge statistics like average length of stay, death rates, autopsy rates, infection rates, and consultation rates calculated from data accumulated when patients are discharged.
HIM / MR practitioners also participate in generating quality reports which may be used for the purpose of improving customer service, quality of patient care, or overall operational efficiency. Examples of aggregate data that relate to quality reports include:
- customer service – the average time it takes to get an appointment at a clinic and the average referral volume by the doctor
- quality of patient care -clinical laboratory quality control data may be analyzed weekly to meet local regulations, and patient fall data may be analyzed monthly if falls are infrequent, infection rates, unplanned returns to the operating room
- overall operational efficiency – cost per case, average reimbursement by Diagnosis Related Groups (DRG), and staffing levels by patient acuity
HIM / MR practitioners in a hospital routinely gather such data to produce easy-to-use ad hoc statistical reports and trend analyses reporting that is available with the hospital’s databases which gives them access to any number of summary reports based on the data elements collected during the patient encounter. Such statistics are frequently used to describe the characteristics of the patients within a hospital and also provide a basis for planning and monitoring patient services.
Here are some examples I can think of when a hospital determines how often data are aggregated and analysed, the frequency depending on the activity or area being measured, the frequency of measurement, and the hospital’s priorities.
The patient census application is needed daily to provide sufficient day-to-day operations staffing, such as nursing and food service. However, annual or monthly patient census data are needed for the facility’s strategic planning.
Hospital management often wants to know summary information about particular diseases or treatment from the disease and procedure index function generally handled as a component of the patient medical record system or the registration and discharge system. Examples of questions that might be asked are: What is the most common diagnosis in the hospital? What percentage of diabetes patients are of a particular ethic group? What is the most common procedure performed on patients admitted with gastritis (or heart attack or any other diagnosis)? Here the process under study is related to the frequency of data analysis of diseases and procedures and the retrieval of information is based on the International Classification of Diseases (ICD) and procedure codes that are collected and entered into discharge system on a daily frequency by HIM / MR practitioners. Such summary information to meet the hospital’s internal requirements could be required for example on an ad hoc basis or daily or weekly or monthly period – which is the frequency of data analysis.
Another type of aggregate information that can be created on an ad hoc basis are register lists that generally contain the names, and sometimes other identifying information, of patients seen in a particular area of the hospital, for example numbers of patients seen in the emergency department or operating room.
Specialised trauma and tumor registries found in hospitals with high-level trauma or cancer centers are used to track information about patients over time and to collect detailed information for research purposes.
If your hospital is at the point of then what I have tried to bring in this post when (JCI, 2010 p. ) “the aggregation of data at points in time enables a hospital to judge a particular process’s stability or a particular outcome’s predictability in relation to expectations”, is truly relevant to the Joint Commission International (JCI) Standard QPS.4.1 which states that “The frequency of data analysis is appropriate to the process being studied and meets organization requirements.” if your hospital had acquired JCI accreditation status or one that is seeking JCI accreditation status.
Nevertheless, regardless of the type of hospital you work at, HIM / MR practitioners must perform the frequency of data analysis appropriate to the process being studied and ensure that the data analysis meets their hospital’s requirements.
References:
Joint Commission International 2010, Joint Commission International Accreditation Standards For Hospitals, 4th edn, JCI, USA
Michelle, AG & Mary, JB 2011, Essentials of Health Information Management: Principles and Practices, 2nd edn, Delmar, Cengage Learning, NY, USA
Wager, KA, Frances, WL & John PG 2005, Managing health care information systems : a practical approach for health care executives,1st edn, Jossey-Bass A Wiley Imprint, San Francisco, CA, USA
