ICD 10 & ICD 11 Development – How, What, Why & When

I have enrolled as an International Classification of Diseases, 11th Revision Beta phase participant. To participate proactively, I will have to make comments, make proposals, propose definitions of diseases in a structured way, will be given a chance to participate in Field Trials, and perhaps assist in translating ICD into other languages. This is not going to be an easy thing to do and one definitely needs knowledge of the ICD. Having worked with ICD 10, I will have to use my ICD 10 experiences and try to contribute to the Beta phase.

So here is the first post from what will be a series of posts I shall blog about as I explore what is going on in the development of ICD 11.

Below is an infographic I painted to begin my first post. The infographic (you can view a larger image by first clicking on the image below which will open in a new tab of your current window and then clicking again on the image in the new tab) summarises facts I have found from the reference list below. They are by no means exhaustive.
References:
Can, Ç 2007, Production of ICD-11:The overall revision process, viewed 20 December 2012, < http://www.who.int/classifications/icd/ICDRevision.pdf >

James, H, ICD-11 in eleven points An update, Research Centre for Injury Studies • Flinders University, Adelaide, viewed 23 December 2012, < http://dxrevisionwatch.files.wordpress.com/2012/07/harrisonslidesamdigumd2011.pdf >

International Statistical Classification of Diseases and Related Health Problems, Volume 2 Instruction manual 2011, 2010 edn, World Health Organization, Geneva, Switzerland

World Health Organization, 2012, Classifications, viewed 18 December 2012, < http://www.who.int/classifications/icd/revision/en/ >

The frequency of data analysis

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:

  1. 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.
  2. 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:

  1. customer service – the average time it takes to get an appointment at a clinic and the average referral volume by the doctor
  2. 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
  3. 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

Big Data – Big Data Basics

Big Data 3Vs cardboard-box-icon

This post is to continue from the introductory post Big Data – Introduction (this link will open in a new tab of your current browser window) on Big Data about the “3Vs” that define Big Data. As I researched the subject of Big Data, three terms – Volume, Velocity and Variety stood out in relation to the “3Vs” of Big Data which leads me to explain to you in this post the widely accepted definition of Big Data from Gartner (the world’s leading information technology research and advisory company) analyst Doug Laney who has characterised Big Data as “data that’s an order of magnitude greater than data you’re accustomed to.”

Accordingly, this “3Vs” model for describing Big Data spans three dimensions, data increasing in volume (amount of data), velocity (speed of data in and out), and variety (range of data types and sources).

The first dimension/characteristic, Volume is about how Ed Dumbill, program chair for the O’Reilly Strata Conference (the leading event that offers the nuts-and-bolts of building a data-driven business – the latest on the skills, tools, and technologies you need to make data work and bringing together practitioners, researchers, IT leaders and entrepreneurs to discuss big data, Hadoop, analytics, visualisation and data markets –  the people and technology driving the data revolution), describes Big Data as “data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the strictures of your database architectures. To gain value from this data, you must choose an alternative way to process it.”

To give you an idea of the volume of data that is increasing exponentially on an annual basis, customer transactions at Walmart is reported to estimate to more than 2.5 petabytes of data every hour. Perhaps these infographics, courtesy of the online storage site Mozy, and Cisco will help you visualise the meaning of pentabytes of data and how it expands further into zettabytes sometime into the future.

Visualizing The Pentabyte Age

Infographic credit : http://mozy.com/blog/misc/how-much-is-a-petabyte/

The Internet in 2015

Infographic credit : http://blogs.cisco.com/news/the-dawn-of-the-zettabyte-era-infographic/

Velocity, the second dimension/characteristic describes the frequency at which data is generated, captured and shared in every imaginable device that all produce torrents of data.

I am sure you have heard of a batch process that takes a chunk of data, submits a job to the server and waits for delivery of the result. In a batch process, the incoming data rate is slower than the batch processing rate but the result is useful despite the delay. For many new applications sources of data, the batch process is just not possible anymore since the speed of data creation is even more important  than the volume. The data is now real-time or nearly real-time  information streaming into the server in a continuous fashion.

The available data in the world today comes from everywhere, this Variety, the third dimension/characteristic signifies the proliferation of data types that add new data types  which no longer fits into neat, easy to consume structures of traditional transactional data, all of which exists as a by-product of ordinary  operations: those being generated by humans from posts to social media sites, digital pictures and videos, purchase transaction records, and GPS signals from cell phones, and from “sensor” data generated from computers and network devices and embedded chips used to gather climate information, from refrigerators and airplanes to bodily implants, and more.

The International Business Machines Corporation (IBM) adds Veracity as the fourth dimension of Big Data. Veracity is when the confidence of the quality (precision and accuracy) of the variety and number of information sources is doubted.

I guess this is enough to known briefly about the basics of Big Data.

References:
About 2012, O’Reilly Strata Conference, viewed 13 December 2012, < http://strataconf.com/strata2012/public/content/about >

Andrew, M & Erik, B 2012, Big Data: The Management Revolution, Harvard Business Review October 2012, Boston, MA, USA

Dave, F 2012, The 3 I’s Of Big Data, Forbes, viewed 13 December 2012,
< http://www.forbes.com/sites/davefeinleib/2012/07/09/the-3-is-of-big-data/ >

Diya, S 2012, The 3Vs that define Big Data, Data Science Central, viewed 13 December 2012, < http://www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data >

Lorraine, F, Michele, O’C,  & Victoria, W 2012, Data, Bigger Outcomes, American Health Information Management Association, viewed 18 November 2012,
< http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_049741.hcsp?dDocName=bok1_049741 >

Stefan, S 2012, The 3 V of BIG Data, Agile Commerce, viewed 13 December 2012,
< http://multichannel-retailing.com/2012/05/the-3-v-of-big-data/ >

What is big data? 2012, International Business Machines Corporation (IBM), viewed 18 November 2012, < http://www-01.ibm.com/software/data/bigdata/ >

Medical and Nursing assessments in 24 hours, updates if less than 30 days old

My purpose of writing this post is to highlight that the Medical Records Review Tool (MMRT) form contains a provision to check for compliance to “Medical assessment in 24 hours. Updates if less than 30 days old. Nursing assessment in 24 hours” documentation in a medical record during a Medical Records Review (MMR) session.

Members of a MMR session must be able to connect this provision found in the MMRT form to the Joint Commission International (JCI) Standard AOP.1.4.1 which requires that “The initial medical and nursing assessments are completed within the first 24 hours after the patient’s admission as an inpatient or earlier as indicated by the patient’s condition or hospital policy.”

However, most members of the MMR session are usually unaware of this requirement, and it is the duty of the team leader to explain this standard which requires that to begin correct treatment for a patient as quickly as possible, the initial assessments must be completed as rapidly as possible.

Members of the MMR session must be breifed that the hospital determines the time frame for completing assessments, in particular the medical and nursing assessments depending on a variety of factors including:

  1. the types of patients cared for by the hospital,
  2. the complexity and duration of their care, and
  3. the dynamics of conditions surrounding their care.

Nonetheless, it is important for the team leader to stress that all initial medical and nursing assessments must be completed within 24 hours of admission to the hospital and available for use by all those caring for the patient.

The team leader must also indentify situations when the patient’s condition indicates, that the initial medical and/or nursing assessment are conducted and available earlier and supported by a hospital policy which define that certain other patient groups are assessed sooner than 24 hours.

Such certain other patient groups who are assessed sooner than 24 hours will include:

  1. emergency patients
  2. patients seen in a consultant’s private office or other outpatient setting prior to care in the hospital as an inpatient

The above certain other patient groups will be assessed within different time frames as follows :

  1. emergency patients are assessed immediately
  2. when the initial medical assessment is conducted in a consultant’s private office or other outpatient setting prior to care in the hospital as an inpatient, it must be no older than 30 days but (i) if the medical assessment is more than 30 days old, then the medical history must be updated and the physical examination repeated and (ii) if the medical assessment is less than 30 days old but if at the time of admission there are significant changes in the patient’s condition since the assessment was first done, then they are noted in the patient’s medical record at the time of admission to inpatient status.

The team leader may include to explain the rationale why the above 30 days time frame applies when the assessment is completed in a consultant’s private office or other outpatient setting prior to care in the hospital as an inpatient. Such explanation may include (JCI, 2010 p. 80) “the critical nature of the findings, the complexity of the patient, and the planned care and treatment (for example, the review confirms the clarity of the diagnosis and any planned procedures or treatments; the presence of radiographs needed in surgery; any change[s] in the patient’s condition, such as control of blood sugar; and identifies any critical lab tests that may need repeating)”, findings by any qualified individual (medical, nursing, and other individuals and services responsible for patient care) who usually will update and/or re-examine this patient group.

Reader can relate this post to the previous post Assessments within 24 hours (this link will open in a new tab of your current browser window) on the JCI Standard AOP.1.5 which states that “Assessment findings are documented in the patient’s record and readily available to those responsible for the patient’s care.”

References:
Joint Commission International, 2010, Joint Commission International Accreditation Standards For Hospitals, 4th edn, JCI, USA

JCI Standard MCI.20.1, ME 1 (Part 2) – infection prevention and control, in “The organization has a process to aggregate data in response to identified user needs.”

OLYMPUS DIGITAL CAMERA

Image credit : http://www.tsft.nhs.uk/

As I had posted in the post JCI Standard MCI.20.1 – patient based data and aggregate data, in a process available to aggregate data to meet the needs of internal and external users (this link will open in a new tab of your current browser window), in this post I shall continue on infection prevention and control. This post is also a follow-up from the previous post on risk management in JCI Standard MCI.20.1, ME 1 (Part 1) – risk management, in “The organization has a process to aggregate data in response to identified user needs.” (this link will open in a new tab of your current browser window).

Infection prevention and control is one of a hospital’s four (4) performance improvement (PI) activities other than risk management, utility system management, and utilisation review PI activities a hospital is required to meet the Joint Commission International (JCI) Standard MCI.20.1, Measurable Element (ME) 1 which requires that a hospital as “The organization has a process to aggregate data in response to identified user needs.”

Although the details of infection prevention control are beyond the scope of this post and blog, I shall embark to highlight some aspects of infection prevention and control here. It is going to be a long post.

Health care–associated infections (HAIs) or also referred to as health care–acquired Infections, are infections acquired in the hospital or other health care facilities that were not present or incubating at the time of the patient’s admission. Hospital (or ‘nosocomial’) infection is infection acquired either by patients while they are in hospital, or by members of hospital staff.  (eds. Adam & Christina 2009) define the term infection as “generally used to refer to the deposition and multiplication of bacteria and other micro-organisms in tissues or on surfaces of the body with an associated tissue reaction.”

At the time of the patient’s admission due to an illness – which impairs the body’s normal defense mechanisms, often the reason for hospital admission, the patient is in the state of risk for infection in which the patient is at increased risk for being invaded by pathogenic organisms because the patient has not been exposed to in the past what the hospital environment now provides the exposure to a variety of virulent organisms, therefore the patient has not developed any resistance to these organisms.

Health care personnel in hospitals who usually fail (eds. Adam & Christina 2009) to practice proper handwashing procedures or to change gloves between patient contacts, contribute to most HAIs been transmitted  to hospitalised patients who are at risk from the most common HAI endemic infections in hospitals caused by multi-resistant tuberculosis, Clostridium difficile one of the major hospital infections in the elderly, vancomycin-resistant enterococci in some specialised units, and cross-infection with methicillin-resistant Staphylococcus aureus (MRSA) that affect the urinary tract, upper and lower respiratory tracts, gastrointestinal tract, conjunctiva, and skin.

HAIs have received increased attention due to their overwhelming consequences in terms of cost, morbidity, and mortality.  One of the reasons for this increased attention is that these infections which are preventable through the adherence to numerous strict guidelines, legal requirements and other recommendations when caring for patients, is that they frequently occur in people whose health is already compromised by disease, age, or injury.

The data presented in the 1999 Institute of Medicine (IOM) study reported that an estimate of  between 44,000 and 98,000 patients die as the result of preventable medical errors in hospitals each year and also reported that hospital-acquired infections, many of which can be prevented, take another 100,000 lives.

In the United States of America, payers have begun to refuse reimbursement for additional care resulting from treatment for an infection not present on admission with the underlying rationale that HAIs are preventable complications and denying reimbursement provides a strong incentive for quality improvement actions to avert them.

Then there are site-specific infection prevention to reduce (i) postoperative surgical wound infections through the use of appropriate surgical site preparation and also prophylactic antibiotic therapy, (ii) ventilator-associated pneumonia by for example minimizing the duration of intubation, (iii) central venous catheter infections for example with the use of sterile technique and full barrier precautions, (iv) urinary tract infection by avoiding unnecessary or prolonged use of indwelling bladder catheters, and (v) resistant organisms for example methicillin-resistant Staphylococcus aureus (MRSA) by employing (a) active surveillance procedures in which cultures are routinely obtained at scheduled intervals to promote earlier identification of resistant organisms, and (b) careful management of antibiotic use.

To address each type of HAI, many hospitals have adopted a series of practices called a “bundle” at a significant cost,  failure to use all the measures prescribed in the “bundle”, for example in the approach to preventing central line-associated bloodstream infections  (CLBSI) (this bundle includes the entire procedure for insertion, the daily cleaning protocols, and the protocols for use of the central line catheter) may adversely affect patient outcomes but adopting a “bundle” has been shown to decrease the incidence of the target infection, and thus been effective  in improving quality of care which may then offset the significant cost.

Transmission of infection as an occcupational hazard in all hospital settings is a major concern when caring for infected patients made worse by the presence of resistant organisms which causes extra concern and makes treatment difficult.

Universal precautions are usually mandated for use with patients who pose the hidden danger when they have not been diagnosed as having an infection and for whom specific infection control measures have therefore not been prescribed. Universal precautions is a critical protective strategy with measures that include hand decontamination upon entering and leaving every patient encounter, isolation and the use of disposable gowns and gloves in addition to hand decontamination for patients with certain particularly dangerous types of infections. Provision of sharps containers wherever needles were used and the provision of a supply of gloves and protective eyewear for employee use are some other measures as part of universal precautions.

Blood-borne pathogens are not the only pathogens of concern in the healthcare environment. Body Substance Precautions are also used in all hospital settings to protect patients and staff members from infections that might be transmitted by any body substance, for example to protect staff members from the tuberculosis (TB) organism.

Confidentiality should be maintained at all times by Health Information Management (HIM) / Medical Records (MR) practitioners who may be needed to provide medical records of staff members exposed to HBV, HCV and HIV infection for review at the time of exposure of the source of their occupational exposure to the bloodborne pathogens including results of blood tests, admitting diagnosis and past medical history.

HIM / MR practitioners may be needed to work closely with an infection control officer at most hospitals which usually designate this officer who has the expertise to guide the staff in planning appropriate infection control procedures to protect staff members from blood-borne pathogens to prevent the spread of HIV, hepatitis B, and other such blood-borne pathogens.

HIM / MR practitioners may be involved in the development of policies and procedures is a key role for any infection control team. The central document is a collection of procedures (sometimes called an infection control policy or infection control manual).

As I have said in my previous posts, most hospitals today are involved in processes of quality improvement.

In the context of HAI, (eds. Adam & Christina 2009,  p. 5) defines ‘surveillance which is a vital component of infection control as ‘the ongoing systematic collection and analysis of data about a disease (or organism) that can lead to action being taken to control or prevent the disease.’

As part of these processes, ongoing data are collected and analysed for problems or opportunities for improvement including using infection control and quality improvement data to improve care. An example of the use of infection control data reviewed from interviews in regard to care practices for patients with catheters in an intensive care unit (ICU) about the series of urinary tract infections for example by the same strain of Serratia as the infective agent that had been identified in all patients in that unit, showed that a deviation from the standard protocol for the unit with the use of one measuring container used by an infected patient cultured positive for the Serratia, and using it from patient to patient easily had transmitted the organism to another patient’s catheter, and the infectious agent could have been spread from patient to patient in this manner.

Quality of care aggregate data takes many forms, revealing such things as infection rates and unplanned returns to the operating room. Infection rates for example MRSA wound infections per 1000 bed days or per 1000 admissions are commonly computed rates like other rates for example average length of stay, based on discharge statistics data that are accumulated when patients are discharged. At the local level, (eds. Adam & Christina 2009) infection rates from surgical wound infections fed back to practising surgeons can demonstrate results in lowering infection rates.

Other forms quality of care aggregate data on HAIs is the reporting of infections.

A daily report generated by a laboratory-based system is able to give information based around ‘alert’ organisms that have the potential to cause outbreaks, for example the percentage of Staphylococcus aureus that are methicillin resistant and/or the percentage of wound swabs showing S. aureus.

Reporting is generated as recommended by (eds. Adam & Christina 2009) through (i) weekly reports by the Infection Control Nurse (ICN) and sent to the wards, departments and clinicians containing  information on alert organisms and infectious patients including simple graphs that provide rapid feedback on current issues while they are still fresh, (ii) monthly reports sent to all members of the Infection Control Team (ICT) within two or three days of the new calendar month, (iii) quarterly reports that includes recommendations to management and education data on who attends the sessions, and (iv) a comprehensive annual report intended for the board members.

Local data must include ‘details’ of wards and consultants – to establish the ‘ownership’ of the data as well as the competitive element,  needs to be analysed promptly and sent to the ward/clinician as daily and weekly reports.

All of the above are my observations, experiences and readings on infection prevention and control activities and processes in a hospital setting to aggregate data in response to identified user needs. They are by no means complete, in future posts I shall document on latest trends and developments in infection prevention and control activities.

In my next post on JCI Standard MCI.20.1, ME 1 I shall dwell on utilisation review PI activities a hospital is required to meet the JCI) Standard MCI.20.1, ME 1.

References:
Adam, PF & Christina, B (eds.) 2009, Ayliffe’s Control of Healthcare-Associated Infection A practical: handbook, 5th edn, Hodder Arnold, London, UK

Caroline, BR & Mary, TK 2012, Textbook of basic nursing, 10th edn, Wolters Kluwer Health, Lippincott Williams & Wilkins, Philadelphia, USA

Janice, RE, Celia, LH 2012, Nursing in todays world : trends, issues & management, 10th edn, Wolters Kluwer Health | Lippincott Williams & Wilkins, Philadelphia, PA, USA

Joint Commission International 2010, Joint Commission International Accreditation Standards For Hospitals, 4th edn, JCI, USA