Question

What are four indicators that you can use to determine when strategies are not having the desired result?

Answer 1

                                   FOUR INDICATORS

                 Quality Indicators (QIs) are standardized, evidence-based measures of health care quality that can be used with readily available hospital inpatient administrative data to measure and track clinical performance and outcomes. An indicator is a 'measurable element of practice permeance for which there is evidence or consensus that it can be used to assess the quality, and hence change in the quality, of care provided.

               Systems of Quality Assurance are necessary, partly to advance service and professional development, and partly to provide accountability. Such systems require criteria and standards on the basis of which to conduct evaluation, but these are not easy to establish. Not only is there a tension between measurability and relevance, there is also variation in the appropriateness of different criteria between localities and countries. With increasing involvement of external evaluation, and increasing interest in international comparisons, there is concern over the validity of many criteria and standards, and over their inappropriate use. The literature has been reviewed, and a series of consensus meetings held by representatives of eleven European countries. Since criteria and standards are so difficult to agree and vary so widely with different contexts of care, it is necessary first to define and identify indicators of care which are likely to be valid across varying localities and countries. Criteria and standards can then be derived from these indicators.

Criteria used to evaluate potential Quality Indicators

Face validity: An adequate quality indicator must have sound clinical or empirical rationale for its use. It should measure an important aspect of quality that is subject to provider or health care system control.

Precision: An adequate quality indicator should have relatively large variation among providers or areas that is not due to random variation or patient characteristics. This criterion measures the impact of chance on apparent provider or community health system performance.

Minimum bias: The indicator should not be affected by systematic differences in patient case mix, including disease severity and comorbidity. In cases where such systematic differences exist, an adequate risk-adjustment system should be possible using available data.

Construct validity: The indicator should be related to other indicators or measures intended to measure the same or related aspects of quality. For example, improved performance on measures of inpatient care (such as adherence to specific evidence-based treatment guidelines) ought to be associated with reduced patient complication rates.

Fosters real quality improvement: The indicator should be robust to possible provider manipulation of the system. In other words, the indicator should be insulated from perverse incentives for providers to improve their reported performance by avoiding difficult or complex cases, or by other responses that do not improve quality of care.

Application: The indicator should have been used in the past or have high potential for working well with other indicators. Sometimes looking at groups of indicators together is likely to provide a more complete picture of quality.

            

                The Quality Indicators (QIs) developed and maintained by the Agency for Healthcare Research and Quality (AHRQ) are one response to the need for multidimensional, accessible quality measures that can be used to gage performance in health care. The QIs are evidence based and can be used to identify variations in the quality of care provided on both an inpatient and outpatient basis. four quality indicators are;

1) Prevention Quality Indicators (PQIs)

2) Inpatient Quality Indicators (IQIs),

3) Patient Safety Indicators, and

4) Paediatric Quality Indicators (PDIs).

    1) Prevention Quality Indicators (PQIs)

The AHRQ PQIs are one set of quality measures that can be used to identify potential problems; follow trends over time; and ascertain disparities across regions, communities, and providers. This module focuses on preventive care services—outpatient services that assist individuals with either staying healthy or managing chronic illness. In these instances, inpatient data can provide information on admissions for ambulatory sensitive conditions that evidence suggests could have been avoided, at least in part through better outpatient care. For example, patients with diabetes may be hospitalized due to complications for their disease if their conditions have not been adequately monitored or if they do not receive education that would allow them to self-manage the disease. There are currently 14 PQIs, listed in Table that measure rates of admissions to the hospital.

         Prevention Quality Indicators

Diabetes short-term complication admission rate Perforated appendix admission rate Diabetes long-term complication admission rate Chronic obstructive pulmonary disease admission rate Hypertension admission rate Congestive heart failure admission rate Low birth weight rate Dehydration admission rate Bacterial pneumonia admission rate Urinary tract infection admission rate Angina admission without procedure Uncontrolled diabetes admission rate Adult asthma admission rate Rate of lower-extremity amputation among patients with diabetes

               Factors such as poor environmental conditions or lack of patient adherence to treatment regimens can result in hospitalization. However, the PQIs provide a good starting point to assess quality of services within a community. The POIs can be used to provide a picture of health care in the community by identifying unmet needs, monitoring how well complications are being avoided in the outpatient setting, assessing access to health care, and comparing the performance of local health care systems across communities.

                The PQIs represent the current state of the art in assessing the health care system as a whole, but particularly in the area of ambulatory care, for example, in preventing medical complications for both acute illness and chronic conditions. The PQIs are valuable when calculated at the population or area level and when used by organizations such as public health groups, State data organizations, health plans, large health systems, and other organizations concerned with the health of populations. The PQIs are risk adjusted for age and gender and provide information about potential problems in the community that may require further analysis. The PQIs help answer questions such as;

• Does the admission rate for diabetes complications in my community suggest a problem in the provision of appropriate outpatient care to this population?
• How does the admission rate for congestive heart failure vary over time and from one region of the country to another?

                These are just a few of the questions that the PQIs can address to assist those health care providers with responsibility for the health of a particular population. The PQIs allow for comparisons across States, regions, and local communities over time. The PQIs do not measure hospital quality, but reflect the care provided in the community.

Despite their strengths, there are several considerations when using these indicators. Differences in PQI rates can explain some of the variation across areas but not all. The complexity of the relationship between socioeconomic status and PQI rates makes it difficult to delineate how much of the observed relationships are due to true access to care issues, difficulties in potentially underserved populations, or other patient characteristics unrelated to quality of care that vary systematically by socioeconomic status. Second, the evidence related to potentially avoidable hospital admissions is limited for each indicator because many of the indicators have been developed as parts of sets. Finally, despite the relationships demonstrated at the patient level between higher quality ambulatory care and lower rates of hospital admission, few studies have directly addressed the question of whether effective treatments in outpatient settings would reduce the overall incidence of hospitalizations.

2)The Inpatient Quality Indicators (IQIs)

The AHRQ IQIs provide information about the quality of medical care delivered in a hospital. This measure set represents the state of the art in measuring the quality of hospital care using inpatient administrative data. The IQIs include measures in the areas of inpatient mortality; utilization of procedures for which there are questions of overuse, underuse, or misuse; and volume of procedures for which there is evidence that a higher volume is associated with lower mortality.

The IQIs that focus on volume are proxy measures of quality and represent counts of admissions in which these procedures were performed. They are based on evidence suggesting that hospitals that perform more of certain procedures—for example, those that are intensive, high-technology, or highly complex—may have better outcomes for those procedures. The provider-level volume IQIs are:

• Oesophageal resection volume
• Pancreatic resection volume
• Abdominal aortic aneurysm (AAA) repair volume
• Coronary artery bypass graft (CABG) volume
• Percutaneous transluminal coronary angioplasty (PTCA) volume
• Carotid endarterectomy (CEA) volume

The mortality indicators for inpatient procedures cover procedures for which mortality has been shown to vary across institutions and for which there is evidence that high mortality may be associated with poorer quality of care. The mortality indicators for inpatient surgical procedures are:

• Oesophageal resection mortality rate
• Pancreatic resection mortality rate
• AAA repair mortality rate
• CABG mortality rate
• PTCA mortality rate
• CEA mortality rate
• Craniotomy mortality rate
• Hip replacement mortality rate

When evaluating mortality rates, the corresponding volumes should be examined in conjunction with the mortality rate because that provides more information about the care delivered. For example, oesophageal resection is a complex surgery, and studies have noted that providers with higher volumes have lower mortality rates. These results suggest that providers with higher volumes have some characteristics, either structurally or with regard to processes that influence mortality.

The mortality indicators for inpatient conditions cover conditions for which mortality has been shown to vary substantially across institutions and for which evidence suggests that high mortality may be associated with deficiencies in the quality of care. The mortality indicators for inpatient medical conditions are:

• Acute myocardial infarction (AMI) mortality rate
• AMI mortality rate, without transfer cases
• Congestive heart failure mortality rate
• Acute stroke mortality rate
• Gastrointestinal haemorrhage mortality rate
• Hip fracture mortality rate
• Pneumonia mortality rate

Also included in the IQIs are utilization indicators that examine procedures whose use varies significantly across hospitals and for which questions have been raised about overuse, underuse, or misuse. High or low rates for these indicators are likely to represent inappropriate or inefficient delivery of care. The procedure utilization indicators are:

• Caesarean section delivery rate
• Primary caesarean delivery rate
• Vaginal birth after caesarean (VBAC) rate, all
• VBAC rate, uncomplicated
• Laparoscopic cholecystectomy rate
• Incidental appendectomy in the elderly rate
• Bilateral cardiac catheterization rate

There are currently 28 IQIs that are measured at the provider or hospital level, as well as 4 area-level indicators that are suited for use at the population or regional level. These 4 indicators, which are utilization measures, include:

• CABG area rate
• Hysterectomy area rate
• Laminectomy or spinal fusion area rate
• PTCA area rate

The IQIs can be used by a variety of stakeholders in the health care arena to improve quality of care at the level of individual hospitals, the community, the State, or the Nation. The IQIs represent advancement in assessing quality of care using hospital administrative data. While these data are relatively inexpensive and convenient to use and represent a rich data source that can provide valuable information, like other data sources that have various limitations, the data should be used carefully when assessing and interpreting the quality of health care within an institution.

3) Patient Safety Indicators (PSIs)

   The PSIs are a set of quality measures that use hospital inpatient discharge data to provide a perspective on patient safety. Specifically, the PSIs identify problems that patients experience through contact with the health care system and that are likely amenable to prevention by implementing system level changes. The problems identified are referred to as complications or adverse events. There are currently 27 PSIs that are defined on two levels: the provider level and the area level. They are risk adjusted using a model that incorporates DRGs (with and without complications aggregated); a modified comorbidity index based on a list developed by Exhauster and colleagues; and age, sex, and age-sex interactions.

At the provider level, the PSIs present a picture of patient safety within a hospital and provide information about the potentially preventable complication for patients who received their initial care and experienced the complication of care within the same hospitalization. The PSIs use secondary diagnosis ICD-9-CM codes to detect complications and adverse events. The measure set covers a variety of areas such as selected postoperative complications, selected technical adverse events, technical difficulty with procedures, and obstetric trauma and birth trauma. The 20 provider-level PSIs include:

• Postoperative pulmonary embolism or deep vein thrombosis
• Postoperative respiratory failure
• Postoperative sepsis
• Postoperative physiologic and metabolic derangements
• Postoperative abdominopelvic wound dehiscence
• Postoperative hip fracture
• Postoperative haemorrhage or hematoma
• Decubitus ulcer
• Selected infections due to medical care
• Iatrogenic pneumothorax
• Accidental puncture or laceration
• Foreign body left in during procedure
• Birth trauma—injury to neonate
• Obstetric trauma—vaginal delivery with instrument
• Obstetric trauma—vaginal delivery without instrument
• Obstetric trauma—caesarean section delivery
• Complications of anaesthesia
• Death in low-mortality DRGs
• Death among surgical inpatients with treatable serious complications (previously known as Failure to rescue)
• Transfusion reaction (AB/Rh)

The area-level PSIs capture all cases of the potentially preventable complications that occur in a given area (e.g., metropolitan service areas or counties), either during hospitalization or resulting in subsequent hospitalizations. They are specified to include the principal diagnosis, as well as secondary diagnoses, for the complications of care. The measurement specifications add cases where a patient’s risk of the complication occurred in a separate hospitalization. The seven area-level PSIs are:

• Foreign body left in during procedure
• Iatrogenic pneumothorax
• Selected infections due to medical care
• Postoperative wound dehiscence in abdominopelvic surgical patients
• Accidental puncture or laceration
• Transfusion reaction
• Postoperative haemorrhage or hematoma

Widespread consensus exists that health care organizations can reduce patient injuries by improving the environment for safety—from implementing technical changes, such as electronic medical record systems, to improving staff awareness of patient safety risks. Clinical process interventions also present strong evidence for reducing the risk of adverse events related to a patient’s exposure to hospital care. These PSIs can be used to better prioritize and evaluate local and national initiatives. Some potential actions, after an in-depth analysis of the system and process of care, include the following:

• Review and synthesize the evidence base and best practices from scientific literature.
• Work with the multiple disciplines and departments involved in care of surgical patients to redesign care based on best practices with an emphasis on coordination and collaboration.
• Evaluate information technology solutions.
• Implement performance measurements for improvement and accountability.

The ability to assess all patients at risk for a particular patient safety problem, along with the relative low cost of collecting the data, are particular strengths of the datasets that use administrative data. However, many important areas of interest, such as adverse drug events, cannot currently be monitored well using administrative data and using this data source to identify patient safety events tends to favour specific types of indicators. For example, the PSIs cited in this chapter contain a large proportion of surgical indicators, rather than medical or psychiatric measures, because medical or psychiatric complications are often difficult to distinguish from comorbidities that are present on admission. In addition, medical populations tend to be more heterogeneous than surgical populations, especially elective surgical populations, making it difficult to account for case mix.

While PSIs may be more applicable to patient safety when limited to elective surgical admissions, the careful use of administrative data holds promises to identify problems for further analysis and study. The limitations of this measure set include those inherent with the use of administrative data, clinical accuracy of the discharged-based diagnosis coding, and indicator discriminatory power. Specifically,

• Administrative data are unlikely to capture all cases of a complication, regardless of the preventability, without false positives and false negatives (sensitivity and specificity).
• When the codes are accurate in defining an event, the clinical vagueness inherent in the description of the code itself (e.g., hypotension) may lead to a highly heterogeneous pool of clinical states represented by that code.
• Incomplete reporting is an issue in the accuracy of any data source used for identifying patient safety problems, as medical providers might fear adverse consequences as a result of full disclosure in potentially public records such as discharge abstracts.
• The heterogeneity of clinical conditions included in some codes, lack of information about event timing available in these datasets, and limited clinical detail for risk adjustment all contribute to the difficulty in identifying complications that represent medical error or that may be at least in some part preventable. These factors may exist for other sources of patient safety data as well. For example, they have been raised in the context of the Joint Commission’s implementation of a sentinel event program geared to identifying serious adverse events that may be related to underlying safety problems.

Yet, despite these issues, the PSIs are a useful tool to identify areas in patient safety that need monitoring and/or intervention for improved patient care.

4)The Paediatric Quality Indicators (PDIs)

           The AHRQ PDIs are a set of quality measures that use hospital administrative data and involve many of the same challenges associated with measure development for the adult population. These challenges include the need to carefully define indicators, establish validity and reliability, detect bias, design appropriate risk adjustment, and overcome challenges of implementation and use. However, as a special population, children require special tailoring of quality measures and risk-adjustment methodologies. The AHRQ PDIs, developed through careful, ongoing research efforts, provide a risk-adjusted tool to identify quality problems for hospitalized children as well as assess the rate of potentially preventable hospitalizations. The AHRQ PDIs currently consist of 18 indicators defined as both provider- and area-level measures. The 13 provider-level PDIs are:

• Accidental puncture and laceration
• Decubitus ulcer
• Foreign body left in during procedure
• Iatrogenic pneumothorax in neonates
• Iatrogenic pneumothorax in non-neonates
• Paediatric heart surgery mortality
• Paediatric heart surgery volume
• Postoperative haemorrhage or hematoma
• Postoperative respiratory failure
• Postoperative sepsis
• Postoperative wound dehiscence
• Selected infections due to medical care
• Transfusion reaction

Existing risk-adjustment strategies for paediatric patients were not suitable for use with the AHRQ PDIs. Most available schemes apply to specific clinical groups and utilize clinical data not available in administrative databases. The APR-DRG methodology, used for risk adjustment in the adult population, was considered for use in the paediatric population. However, using the APR-DRGs could not adjust for complications in the paediatric population because it resulted in over-adjustment. As a result, different risk adjustment strategies were investigated for potential incorporation into the PDIs.

       Three important risk-adjustment factors of significance to the paediatric population were identified:

(1) reason for admission (including principal procedure),

(2) comorbidities

(3) age and gender              .

                 Using a modified-DRG risk adjustment combined with comorbidity adjustment based on the AHRQ Clinical Classification System and age and gender adjustment, the AHRQ PDIs include a novel and specialized risk-adjustment system. They also include stratification, another approach to accounting for case mix. Stratification allows hospitals to identify which segment of the paediatric population accounts for any elevation in rates, creating more user-friendly measures. Tailored stratification schemes are available for six of the PDIs: accidental puncture and laceration, decubitus ulcer, iatrogenic pneumothorax, postoperative haemorrhage or hematoma, postoperative sepsis, and selected infections due to medical care. Despite these efforts to account for risk, it is anticipated that further research on paediatric risk adjustment will be important for assessing quality appropriately.

In addition to the provider-level indicators, the PDIs also include five area-level indicators:

• Asthma admission rate
• Diabetes short-term complication rate
• Gastroenteritis admission rate
• Perforated appendix admission rate
• Urinary tract infection admission rate

These indicators track potentially preventable hospitalizations and allow policymakers to target specific groups that appear to be developing more severe disease requiring hospitalization. Higher-than-anticipated rates may reflect poor access to care (e.g., from lack of insurance or too few primary care physicians), barriers to timely care (e.g., clinics that require daytime appointments), barriers to adherence to medical advice (e.g., language barriers), cultural influences that preclude seeking early treatment, or higher prevalence of poor health behaviours (e.g., smoking). Interventions may address any of these factors.

Area-level indicators are prone to bias due to cultural factors that may be outside of a health system’s control. For instance, an area with a high number of illegal immigrants may have patients presenting with more advanced disease, because patients delay seeking care for fear of deportation. In addition, factors such as smoking or obesity may be more prevalent in certain areas. Risk adjustment should include these factors, and an adjustment for socioeconomic status, as a proxy, and has been included in these PDIs. However, risk adjustment for socioeconomic groups may mask true differences in access to good quality care. For this reason, risk-adjusted rates should be considered alongside raw, unadjusted rates.

                       Characteristics

          A health indicator which will be used internationally to describe global health should have the following characteristics:

It should be defined in such a way that it can be measured uniformly internationally.

It must have statistical validity.

The indicator must be data which can feasibly be collected.

The analysis of the data must result in a recommendation on which people can make changes to improve health.

                

LIST OF HEALTH INDICARORS

                     Health indicators are required in order to measure the health status of people and communities.

              Health indicators are required in order to measure the health status of people and communities.

Health Indicators

• Crude death rate
• Life expectancy
• Infant mortality rate
• Maternal mortality rate
• Proportional mortality rate

Morbidity indicators

• Prevalence
• Incidence
• Others

Health status

Incidence counts of any of the following in a population may be health indicators:

• Low birth weight
• Obesity
• Arthritis
• Diabetes
• Asthma
• High blood pressure
• Cancer incidence
• Chronic pain
• Oral health
• Depression
• hospital visits due to injury
• reports of waterborne diseases or foodborne illness

Disability indicators

• Disability adjusted life years (DALY)
• Others: Activities of daily living (ADL), Musculoskeletal disability (MSD) score etc.

Nutritional indicators

• Proportion of low birth weight
• Prevalence of anaemia
• Proportion of overweight individuals
• Prevalence of underweight among under-fives
• Prevalence of stunting among under-fives
• Prevalence of acute malnutrition among under-fives

Social and mental health indicators

• Alcohol related indicators
• Injury rates

Health system indicators

• Healthcare delivery related
• Health policy indicators
• Health improvement activities

Elements and Performance Criteria

ELEMENT	PERFORMANCE CRITERIA
Elements define the essential outcomes	Performance criteria describe the performance needed to demonstrate achievement of the element.
1. Prepare to implement falls prevention strategies	Determine identified strategies which can be implemented within role and responsibilities and discuss with supervisor or relevant health professional Interpret findings of the assessment and explain relevant information to the older person and their carer clarifying any requirements Seek the older persons’ permission, cooperation and commitment by communicating in a supportive and encouraging manner that is respectful of the older person and their carer's level of understanding, cultural background, needs and rights
2. Identify potential risk of falls	Discuss the older person’s concerns about falling and how they have coped with previous falls in a manner respectful of their privacy, dignity, wishes and beliefs Discuss the support of carers where appropriate Identify and explore lifestyle, health and mobility factors with the older person, that might affect the level of risk Determine the older person’s physical indicators of risk of falls using appropriate tools and methodologies within scope of role Determine the older person’s risk factors based on findings in collaboration with supervisor and/or relevant health professional Identify the older person’s needs, issues and concerns outside scope of practice and refer to appropriate supervisor, health professional or agency in line with organisation procedures
3. Implement falls prevention strategies	Identify and explain options to minimise the risk of falls and include opportunities for the older person and carer to contribute where appropriate Work with the older person and their carers to identify and implement strategies that are consistent with their safety needs, priorities, preferences and specific requirements Implement strategies in a safe and effective manner that minimises the older person’s discomfort In collaboration with the older person and carers, decide how strategies can be tested and how success will be measured and communicated within the support team

Conclusions. Monitoring health care quality is impossible without the use of clinical indicators. They create the basis for quality improvement and prioritization in the health care system. To ensure that reliable and valid clinical indicators are used, they must be designed, defined, and implemented with scientific rigour