APIC guidelines for Infection Control

Infection Control is an important part of hospital quality management and hospital management. Presenting  the APIC ( Association for Professionals in Infection Control and Epidemiology)  guidelines for Infection Control :

http://apic.org/Professional-Practice/Implementation-guides

Risk management in hospitals

Hospitals carry a natural amount of risk in their operations: both clinical, and non-clinical risk. While there exist the apparent clinical risks such as infections, wrong medication, wrong surgery etc, there also exist non- clinical risks such as fire, chemical spillage, electrical hazards etc.

Risk management is an important part of Quality Management and Patient Safety activities in hospitals. The US National Library of Medicine’s controlled vocabulary thesaurus,  MeSH, defines Risk Management as “ the process of minimizing risk to an organization by developing systems to identify and analyze potential hazards to prevent accidents, injuries, and other adverse occurrences, and by attempting to handle events and incidents which do occur in such a manner that their effect and cost are minimized. Effective risk management has its greatest benefits in application to insurance in order to avert or minimize financial liability.”

The management of risks require a proactive approach consisting of  Risk identification, Risk assessment, Risk mitigation, Problem Prioritization, Risk reporting , Risk management, Investigation of adverse events and  Establishment of a safe organizational culture.

An incident reporting policy is required. An important part of risk management is the reporting system for incidents such as adverse events , sentinel events and near misses. Sentinel events, which are events not related to the primary illness, resulting in patient death/ permanent loss of function, may include serious injury such as  loss of limb or function. The number of sentinel events are to be  monitored on a monthly basis and reported to the Quality Steering Committee. Patients are assessed at admission for risk of adverse episodes such as falls, and proactive measures are taken accordingly. It is recommended that the incidents are analysed and  analysis is done , including Root Cause Analysis for Sentinel events. This analysis is used to redesign /modify processes or carry out corrective/ preventive steps.

“Safety First” programme is implemented in many hospitals for vulnerable patients

(patients<16 yrs/ >60 yrs, women in labour, critical care patients, patients unable to perform ADL). In addition, the following patients/ processes are high risk and departmental level precautions are to be taken: Patients undergoing surgery, sedation, blood transfusion, chemotherapy, dialysis.

For long-staying patients, medical board is to be held and communication is to be carried out with the patient’s relatives.

Failure Mode and Effects Analysis (FMEA) is a technique used for proactive risk reduction. It consists of the computation of a RPN ( Risk Probability Number) , which is arrived at by multiplying Severity (S), Occurrence (O) and Detection ( D), i.e. S X O X D. It can be used for a variety of problems such as Medication Errors (MEs), Needle Stick Injuries ( NSIs) etc.

According to Hippocrates, the father of modern medicine, the basic principle of medicine should be “ Primum non nociere” , i.e. “ First do no harm.” Keeping this in mind, Risk management is an activity that should be proactively carried out by hospitals.

Data Data Every Where, But Not A Bit Makes Sense

Details of Author:
Name:  Dr. Gunjan Sharma; Age: 29 years; Qualification:  B.D.S (RGUHS) , PGDHM (ASCI)

Experience: 3 years; Presently working at: Fernandez Hospital, Hyderabad; Department: Quality

Designation: Quality Coordinator; Areas of Interest:    Quality aspects in Indian healthcare industry,       Training needs of Indian healthcare workforce,  Auditing,  Data Management 

In today's healthcare industry everyone is talking about high end information systems and technology solutions like HIS, EMR etc. but the ground reality is far more different than these jargons.

Budding generation of Managers and mandatory rules or standards laid down by various governmental and non governmental bodies in India have sparked the process of data collection in hospitals. Lot of data is available in raw and manual form but most of it is of no use as it cannot be processed for obtaining any inferences.
Major concerns in this area are:

Manual Data

In this computer driven era still lot of data is entered manually. Huge piles of manual data are difficult to handle as it first needs to be digitized. Moreover problems like overwriting, corrections and incomplete data sets are spoiling the quality of collected data.

Lack of Staff

I fail to understand the repulsive attitude of Indian hospitals towards the data entry personnel. It might be due to their cost cutting strategies that they find them to be of no use. Hospitals are more keen in utilizing their existing staff in entering data for their concerned department. I think it’s time for them to realize that data entry is an art and the entire life cycle of data depends on its inception. Bad quality data is the horror of any data research scientist.

Transcription Errors

Even if some of the hospitals recruit data entry operators many transcription errors occur while digitizing the data. One of the major reasons for this can be; untrained data entry operators. Majority of data entry operators are recruited from other industries as there is a lack of staff which is specialized in hospital data and understands healthcare terminologies.

Poor HIS

Most of the hospitals are either buying or developing their own HIS. But there is lack of planning in customizing or developing HIS products as the end users are ignorant about their present and future needs. Lack of training and sensitization of hospital staff towards the statistics driven processes has led to this condition. Hence hospitals end up with HIS which is incomplete and is not able to satisfy the requirements of the departments.

Lack of Analysts

Huge sets of data needs the magic touch of an analyst to transform into sense making graphs and trends. Hospital management courses need to focus more stringently in the area of data analysis by introducing subjects like Business Intelligence. But it’s not just the educational institutes, hospitals also need to motivate and provide opportunity to young managers into the less explored Indian woods of healthcare data.

I hope that this miniscule effort of mine will encourage all upcoming managers and administrators in the area of healthcare data management and analysis.  

Launch of NABH pre- accreditation entry level certification standards for healthcare organisations

NABH plans to launch pre- accreditation entry level certification standards for healthcare organisations , in resource- challenged situations, as a preparation for full NABH accreditation.

Details at : http://nabh.co/main/publiccomments/PRE_ACCREDITATION_EL.asp

The standards are open for discussion and comment.]

Comments may be sent to:

Jatin Kumar
Assistant Director
National Accreditation Board for Hospitals and Healthcare Providers (NABH)
Quality Council of India,
6th Floor, ITPI Building, 4A, Ring Road, IP Estate
New Delhi 110 002, India
Tel: +91-11-23323416-20; Fax: +91 11 23323415
Email: jatin@nabh.co 

 



 

Reliability: The Next Frontier in Patient Safety

Reliability: The Next Frontier in Patient Safety

by Dev Raheja, MS, CSP

Author: Safer Hospital Care 

(Brief author Bio: Dev  Raheja, MS,CSP, author of Safer Hospital Care, is an international risk management, patient safety and quality assurance consultant for Healthcare, medical device, and aerospace industry for over 25 years.  He applies evidence base safety techniques from a variety of industries to healthcare.He is a trainer on how to come up with elegant solutions using creativity and innovation. Being a true international consultant, he has conducted training in several countries and at several universities. He helped a major Midwest company from going out of business to becoming a world leader by eliminating safety mishaps.  Prior to becoming a consultant in 1982 he worked at GE Healthcare as Supervisor of Quality Assurance, and at Booz-Allen & Hamilton as Risk Management consultant for nuclear and mass transportation industry.

He has served as Adjunct Professor at the University of Maryland for five years for its PhD program in Reliability Engineering. Currently he is an Adjunct Professor at the Florida Tech for its BBA degree in Healthcare Management, has authored two more  books Assurance Technologies Principles and Practices , and Zen and the Art of Breakthrough Quality Management. He is Associate Editor- Healthcare Safety for the Journal of System Safety and has written articles for the National Capital Healthcare Executives newsletters. He has received several industry awards including the Scientific Achievement Award and Educator-of-the Year Award from System Safety Society.  He is a former National Malcolm Baldrige Quality Award Examiner for the first batch of examiners.

He majored in Human Factors Engineering as a part of master’s degree in industrial engineering, is a Certified Safety Professional through the Board of Certified Safety Professionals, took training in “Perfecting Patient Care” through the Pittsburgh Regional Health Initiative, an organization supported by 40 hospitals, is a member of the American College of Healthcare Executives, and is a charter member of the Improvement Science Research Network (ISRN) at University of Texas Health Science Center. He serves on the Patient and Families Advisory Council of the Johns Hopkins Hospital and its committee on alarms management.)  

Reliability is the next frontier in patient safety according to Dr. Carolyn Clancy, the former Director of the Agency for Healthcare Research and Quality (AHRQ) and current Assistant Deputy Undersecretary for Health, Quality, Safety and Value, veterans Health Administration. She gave this message as a keynote speaker at the Sixth Annual Forum and Gala of the Lucian Leape Institute of the National Patient Safety Foundation, held in Boston on September 12, 2013.

Hospitals are still far from being highly reliable is a similar high level warning from the Joint Commission, the premier hospital accreditation agency. In an article “High-Reliability Health Care: Getting There from Here” written by The Joint Commission President and CEO Mark R. Chassin, M.D., M.P.H., and executive vice president for healthcare quality evaluation Jerod M. Loeb, Ph.D., they urge hospitals to make the substantial changes that will be needed to achieve the ultimate goal of zero patient harm by adapting lessons from high-risk industries. They report that “too many hospitals and health care leaders currently experience serious safety failures as routine and inevitable parts of daily work. To prevent the harm that results from these failures, which affects millions of Americans each year, the article specifies a framework for major changes involving leadership, safety culture and robust process improvement. This framework is designed to help hospitals make progress toward high reliability, which is the achievement of extremely high levels of safety that are maintained over long periods of time —safety comparable to that demonstrated by the commercial air travel, nuclear power, and amusement park industries.”

Reliability Theory Missing in Healthcare

Medical education usually does not cover the theory of reliability. One cannot blame hospitals to be going in different directions. The Institute of Healthcare Improvement (IHI) has taken the initiative to apply industry methods of system reliability to healthcare systems. It defines reliability as “failure-free performance over time^”. This is simple enough to be understood by anyone. The aim is to have no failures over an extended time period in spite of variability in the patient environment. This is in line with the technical definition of reliability as the probability of successful performance of intended functions for a specified length of time under a specified user (patient) environment. In a system where the severity of consequences is high, such as in hospitals, the goal is to achieve reliability as close to 100% as possible. This is called failure-free performance. Some hospitals have achieved this goal for specific medical procedures for several quarters. Can they extend this performance over years instead of quarters? That depends on many factors such as understanding reliability at senior management level, culture of innovation, effective teamwork, etc.

Roadblocks to Use of Reliability

The failures of the U.S. healthcare system are enormous considering the severity of failures. As much as 100,000 patients die each year from hospital mistakes. Another 2.1 million patients are harmed from nosocomial infections (infections acquired during hospital stay). The cost is in billions. There is very little incentive use reliability measures because the variability in healthcare is enormous compared to the aviation and industrial fields. Each customer (patient) is different and each illness is unique in its own way. Then there are interconnecting systems such as cardiology, gynecology, gastroenterology, emergency medicine, oncology, and patient data from various doctors, pagers, computers, vendor software, and intensive care, each operating independently most of the time.

Good Solutions are Available

We like to offer a good solution hoping that it will be good beginning to improve patient outcomes significantly. A good solution may be to apply system reliability methods to each critical intervention so that the variability is known. For example, if a protocol requires that a patient coming to the ED (emergency department) must get attention within ten minutes of arrival, then the performance can be defined as “patient must be registered with the triage nurse within 10 minutes.” A failure can be defined as “patient waiting longer than 10 minutes”. A woman in a New York hospital died while waiting for an hour in the emergency department. A blood clot in her leg traveled all the way to her brain. All 24 hours were recorded on the hospital video.

The time dimension for reliability can be defined in terms of calendar time such as every three months (quarterly) or every 1000 patients. Then reliability can be measured as the percentage of patients receiving service within 10 minutes during the quarter, or per 1000 patients. IHI is taking a similar approach for patients who need antibiotics within an hour after a surgical procedure; then reliability is measured as the ratio of number of patients receiving the antibiotic within an hour and the number of patients requiring this treatment.

Before we define system reliability, we need to define a medical system. It is a composite, at any level of complexity, of medical equipment, caregivers, medical procedures, lab work, environment, communications, and patients with a specified system mission.  Medical equipment includes CT, MRI, ventilators, artificial hearts, and dialysis machines. People include physicians, residents, interns, attendings, nursing staff, med techs, support associates, administrative personnel, patients, visitors.  Medical procedures include diagnosis, surgery, intensive care, intermediate care, lab procedures, intubations, intra-venous fluid infusions, patient visits, admittance, discharge, emergency patient processing, and trauma support. Communications include patient handoffs, verbal communications and communication among pharmacists, doctors, nurses, residents, patients, pagers, telephones, and computer screens.

Obviously, the mission is a safe and positive experience for patients. Therefore system reliability is the function of the integrated performance of all these. This model is pictorially shown in illustration below and is called a series system.  If any block in the system fails, the whole mission fails.

The chain shows that if any subsystem fails, the mission fails.

We can write the system reliability as the multiplication of all the subsystem reliabilities:

System Reliability = R (patient admittance) x R(diagnosis) x R(treatment) x R(post-discharge follow-up)

In this equation R stands for reliability. A hospital may modify the model if this model is not comprehensive. This model assumes that each of these four subsystems is independent of each other and each must work right. If not, the laws of conditional probability apply. For a calculation of conditional probability, please click here. Numerically, the system reliability in the above model for a defined time (yearly, over 3 years, etc) will then be:

System Reliability = (Percent patients admitted without harm or inconvenience) x (percent patients receiving the right diagnosis the first time) x (percent patients receiving satisfactory treatment) x (percent patients who follow the treatment regimen after discharge)

If the reliability of each of these four subsystems is 90 percent, the system reliability (chance that all of these will perform as intended) would be:

            .90 x .90 x .90 x .90 = .656 or 65.6 percent

To our knowledge no hospital is measuring reliability at the system level. Most of them are applying to a component of a system. The IHI is applying reliability measurements to components such as diagnoses, community acquired pneumonia, heart failure, acute myocardial infraction, hip/knee replacements, and bypass graft surgery. The reliability for each is simply the ratio of patients receiving the right care and the number of patients requiring the care. It may be noted that the system reliability model can be applied at the component level also as long as the components are functions of equipment, people, procedures, environments, and communications. The mission is still the same, safe and positive patient experience.

Contact the Author: Dev Raheja can be contacted at raheja@PatientSystemSafety.com